Senior Manager, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Senior Manager, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. The Boeing Commercial Airplanes (BCA) 787 Interiors organization is seeking multiple Associate Cabin Systems Engineers to join our team in NorthCharleston, South Carolina. At Boeing, we are dedicated to designing and integrating advanced electrical cabin systems to advance the future of our airplane interiors and passenger experience. Our projects focus on translating high-level concepts and requirements into the system design, ensuring the seamless physical integration of electrical systems and components within our aircraft. We collaborate with a global supplier network to implement cutting-edge system hardware and software, validating our designs through rigorous testing. Our engineers work on aircraft systems from initial concept through certification, delivery, and throughout their production lifecycle, continually pushing the boundaries of innovation in commercial air transport. This position will specifically involve working with Cabin Systems, which encompasses interior lighting, passenger address systems, in-flight entertainment, seatback video, passenger connectivity, satellite connections and more. Our teams are currently hiring for a broad range of experience levels including Experienced and Senior Electronic Systems Design and Analysis Engineers. Position Responsibilities: Develops and documents complex electronic and electrical system designs. Tests and validates to ensure system designs meet operational and functional requirements Assists in monitoring supplier performance to ensure system integration and compliance with requirements Solves problems concerning fielded hardware and software over the entire product lifecycle Researches specific technology advances for potential application to company business needs Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering (with a focus in Electrical, Mechanical, or Aeronautical), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement. 3+ years of related work experience or an equivalent combination of education and experience. Preferred Qualifications (Desired Skills/Experience): Experience with Cabin Systems Experience working with suppliers Experience interfacing with E-UMs/the FAA and/or other certification regulatory agencies Exceptional organizational skills with attention to detail. Conflict of Interest: Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process Drug Free Workplace: Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies. Pay Range Summary: At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities. The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements. Please note that the salary information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Summary Pay Range: $91,800 - $124,200 Applications for this position will be accepted until Nov. 13, 2026 Export Control Requirements: This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. 120.62 is required. "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee. Export Control Details: US based job, US Person required Education Bachelor's Degree or Equivalent Required Relocation This position offers relocation based on candidate eligibility. Visa Sponsorship Employer will not sponsor applicants for employment visa status. Shift This position is for 1st shift Equal Opportunity Employer: Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
11/12/2026
Full time
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. The Boeing Commercial Airplanes (BCA) 787 Interiors organization is seeking multiple Associate Cabin Systems Engineers to join our team in NorthCharleston, South Carolina. At Boeing, we are dedicated to designing and integrating advanced electrical cabin systems to advance the future of our airplane interiors and passenger experience. Our projects focus on translating high-level concepts and requirements into the system design, ensuring the seamless physical integration of electrical systems and components within our aircraft. We collaborate with a global supplier network to implement cutting-edge system hardware and software, validating our designs through rigorous testing. Our engineers work on aircraft systems from initial concept through certification, delivery, and throughout their production lifecycle, continually pushing the boundaries of innovation in commercial air transport. This position will specifically involve working with Cabin Systems, which encompasses interior lighting, passenger address systems, in-flight entertainment, seatback video, passenger connectivity, satellite connections and more. Our teams are currently hiring for a broad range of experience levels including Experienced and Senior Electronic Systems Design and Analysis Engineers. Position Responsibilities: Develops and documents complex electronic and electrical system designs. Tests and validates to ensure system designs meet operational and functional requirements Assists in monitoring supplier performance to ensure system integration and compliance with requirements Solves problems concerning fielded hardware and software over the entire product lifecycle Researches specific technology advances for potential application to company business needs Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering (with a focus in Electrical, Mechanical, or Aeronautical), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement. 3+ years of related work experience or an equivalent combination of education and experience. Preferred Qualifications (Desired Skills/Experience): Experience with Cabin Systems Experience working with suppliers Experience interfacing with E-UMs/the FAA and/or other certification regulatory agencies Exceptional organizational skills with attention to detail. Conflict of Interest: Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process Drug Free Workplace: Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies. Pay Range Summary: At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities. The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements. Please note that the salary information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Summary Pay Range: $91,800 - $124,200 Applications for this position will be accepted until Nov. 13, 2026 Export Control Requirements: This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. 120.62 is required. "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee. Export Control Details: US based job, US Person required Education Bachelor's Degree or Equivalent Required Relocation This position offers relocation based on candidate eligibility. Visa Sponsorship Employer will not sponsor applicants for employment visa status. Shift This position is for 1st shift Equal Opportunity Employer: Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field +2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning). +2 years experience leveraging Agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang +2 years Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field +2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning). +2 years experience leveraging Agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang +2 years Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Fellow, Integrated Solutions & Ecosystem Architecture Description - Why this role is critical to HP The next generation of personal computing will be defined across company boundaries. Silicon, operating systems, AI platforms, memory, security, cloud services, firmware and device experiences increasingly evolve on independent roadmaps, yet must operate as one integrated system in the products customers use. HP is seeking a Technical Fellow to serve as the senior technical leader for partner architecture and ecosystem engineering across Personal Systems. This leader will work directly with HP's most strategic technology partners and with engineering teams across HP to turn separate technology roadmaps into integrated, multi-generation product architectures. The role will shape joint technical direction, establish the architectural interfaces and commitments required across organizations, identify where HP should build, integrate or co-engineer, and drive the technology workstreams needed to convert capabilities into differentiated products. This is a critical hands-on senior technical leadership role accountable for architecture, roadmap convergence, technical decisions and co-engineering outcomes across company boundaries. Key responsibilities Lead HP's technical architecture engagement with strategic ecosystem partners across silicon, operating systems, AI platforms, memory and storage, cloud, device technologies and system software. Create integrated multi-generation technology roadmaps connecting partner capabilities, HP engineering priorities and future product requirements; identify dependencies, gaps and critical decisions early enough to influence both HP and partner roadmaps. Define HP's technical asks to partners. Translate customer needs, system requirements and architectural direction into specific partner capabilities, interfaces, engineering commitments and product intercepts. Drive common architecture and leverage across the Personal Systems portfolio. Establish where platforms, interfaces, software components, firmware capabilities, validation methods and system technologies should be common and reusable, while preserving meaningful product differentiation. Lead architecture across organizational boundaries inside HP. Connect device engineering with HP-wide AI, software, security, manageability, services and experience teams so independently developed capabilities come together as complete system solutions. Drive joint technology workstreams from concept through engineering commitment. Establish clear technical outcomes, owners, dependencies, milestones and acceptance criteria with internal teams and external partners; ensure promising technologies progress beyond demonstrations into product-ready capabilities. Shape HP's architecture for next-generation AI and agentic computing. Drive system-level decisions spanning CPU/GPU/NPU execution, memory, power, thermals, firmware, operating systems, AI runtimes, security, manageability and device-edge-cloud integration. Resolve complex cross-company architecture tradeoffs. Provide senior technical judgment where performance, cost, power, memory, security, roadmap timing, product requirements and independently managed partner priorities conflict. Represent HP as a senior technical counterpart with industry leaders. Engage partner CTOs, Fellows, architects and engineering executives to influence technology direction, establish joint priorities and secure engineering commitments. Build HP's partner-architecture capability and technical bench. Lead and mentor a small team of senior architects and technical leaders, develop future technical talent and strengthen HP's ability to operate credibly at the highest levels of the industry. What success looks like HP influences partner roadmaps earlier. Important HP requirements appear in partner architectures, engineering plans and future technology releases rather than being addressed after roadmaps are fixed. Partner engagement produces engineering outcomes. Joint work results in committed resources, interfaces, technology deliverables, reference implementations and capabilities that reach HP products. Architecture converges earlier across HP and its partners. Dependencies and technical tradeoffs are resolved before they become late product issues, reducing duplicated work, redesign and schedule risk. HP gains greater leverage from common architecture. Reusable system capabilities, interfaces and validation approaches are adopted across multiple product lines and generations. Emerging technology translates into product differentiation. New silicon, software, AI and ecosystem capabilities move systematically from evaluation to co-engineering to product adoption. HP becomes a stronger technical voice in the ecosystem. Strategic partners increasingly engage HP as a technology co-designer whose requirements and architecture help shape future platforms. HP builds deeper technical leadership. Senior architecture expertise grows inside the company, with a stronger bench and succession pipeline for critical technical roles. Required experience and capabilities Exceptional record of technical leadership across complex, large-scale computing platforms or product ecosystems. Deep systems architecture expertise spanning several of the following: silicon, operating systems, firmware, system software, AI/ML systems, memory, security, manageability, cloud/edge computing and hardware platforms. Demonstrated experience shaping multi-generation technology roadmaps with major external technology partners. Proven ability to turn emerging technologies and architectural concepts into shipping platforms, products or broadly deployed capabilities. Experience negotiating consequential technical tradeoffs across companies and organizations with different priorities, roadmaps and business models. Strong understanding of system-level performance and the interactions among compute, memory, power, thermals, firmware, software and workload behavior. Executive presence and technical credibility to work effectively with CTOs, Fellows, senior engineering executives and business leaders. Ability to operate effectively with incomplete information, rapidly changing technology and complex organizational dependencies while still driving decisions and execution. Demonstrated ability to lead through influence across organizations where direct reporting authority does not exist. Track record of attracting, mentoring and developing exceptional senior technical talent. Preferred experience Senior architecture leadership in personal computing, semiconductor, operating-system, AI-platform, cloud/edge or large-scale device organizations. Experience working directly with major silicon, operating-system, AI, memory, cloud and device-ecosystem companies. Experience spanning both technology creation and productization-not solely research, standards or product execution. Experience with multi-platform architectures involving multiple silicon vendors, operating environments and product categories. Experience developing joint reference architectures, co-engineering programs, industry standards or major partner-dependent technology initiatives. Advanced degree in Computer Science, Computer Engineering, Electrical Engineering or a related discipline, or equivalent depth of industry experience. The pay range for this role is $350,000 to $450,000 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Engineering Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status . click apply for full job details
11/12/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Fellow, Integrated Solutions & Ecosystem Architecture Description - Why this role is critical to HP The next generation of personal computing will be defined across company boundaries. Silicon, operating systems, AI platforms, memory, security, cloud services, firmware and device experiences increasingly evolve on independent roadmaps, yet must operate as one integrated system in the products customers use. HP is seeking a Technical Fellow to serve as the senior technical leader for partner architecture and ecosystem engineering across Personal Systems. This leader will work directly with HP's most strategic technology partners and with engineering teams across HP to turn separate technology roadmaps into integrated, multi-generation product architectures. The role will shape joint technical direction, establish the architectural interfaces and commitments required across organizations, identify where HP should build, integrate or co-engineer, and drive the technology workstreams needed to convert capabilities into differentiated products. This is a critical hands-on senior technical leadership role accountable for architecture, roadmap convergence, technical decisions and co-engineering outcomes across company boundaries. Key responsibilities Lead HP's technical architecture engagement with strategic ecosystem partners across silicon, operating systems, AI platforms, memory and storage, cloud, device technologies and system software. Create integrated multi-generation technology roadmaps connecting partner capabilities, HP engineering priorities and future product requirements; identify dependencies, gaps and critical decisions early enough to influence both HP and partner roadmaps. Define HP's technical asks to partners. Translate customer needs, system requirements and architectural direction into specific partner capabilities, interfaces, engineering commitments and product intercepts. Drive common architecture and leverage across the Personal Systems portfolio. Establish where platforms, interfaces, software components, firmware capabilities, validation methods and system technologies should be common and reusable, while preserving meaningful product differentiation. Lead architecture across organizational boundaries inside HP. Connect device engineering with HP-wide AI, software, security, manageability, services and experience teams so independently developed capabilities come together as complete system solutions. Drive joint technology workstreams from concept through engineering commitment. Establish clear technical outcomes, owners, dependencies, milestones and acceptance criteria with internal teams and external partners; ensure promising technologies progress beyond demonstrations into product-ready capabilities. Shape HP's architecture for next-generation AI and agentic computing. Drive system-level decisions spanning CPU/GPU/NPU execution, memory, power, thermals, firmware, operating systems, AI runtimes, security, manageability and device-edge-cloud integration. Resolve complex cross-company architecture tradeoffs. Provide senior technical judgment where performance, cost, power, memory, security, roadmap timing, product requirements and independently managed partner priorities conflict. Represent HP as a senior technical counterpart with industry leaders. Engage partner CTOs, Fellows, architects and engineering executives to influence technology direction, establish joint priorities and secure engineering commitments. Build HP's partner-architecture capability and technical bench. Lead and mentor a small team of senior architects and technical leaders, develop future technical talent and strengthen HP's ability to operate credibly at the highest levels of the industry. What success looks like HP influences partner roadmaps earlier. Important HP requirements appear in partner architectures, engineering plans and future technology releases rather than being addressed after roadmaps are fixed. Partner engagement produces engineering outcomes. Joint work results in committed resources, interfaces, technology deliverables, reference implementations and capabilities that reach HP products. Architecture converges earlier across HP and its partners. Dependencies and technical tradeoffs are resolved before they become late product issues, reducing duplicated work, redesign and schedule risk. HP gains greater leverage from common architecture. Reusable system capabilities, interfaces and validation approaches are adopted across multiple product lines and generations. Emerging technology translates into product differentiation. New silicon, software, AI and ecosystem capabilities move systematically from evaluation to co-engineering to product adoption. HP becomes a stronger technical voice in the ecosystem. Strategic partners increasingly engage HP as a technology co-designer whose requirements and architecture help shape future platforms. HP builds deeper technical leadership. Senior architecture expertise grows inside the company, with a stronger bench and succession pipeline for critical technical roles. Required experience and capabilities Exceptional record of technical leadership across complex, large-scale computing platforms or product ecosystems. Deep systems architecture expertise spanning several of the following: silicon, operating systems, firmware, system software, AI/ML systems, memory, security, manageability, cloud/edge computing and hardware platforms. Demonstrated experience shaping multi-generation technology roadmaps with major external technology partners. Proven ability to turn emerging technologies and architectural concepts into shipping platforms, products or broadly deployed capabilities. Experience negotiating consequential technical tradeoffs across companies and organizations with different priorities, roadmaps and business models. Strong understanding of system-level performance and the interactions among compute, memory, power, thermals, firmware, software and workload behavior. Executive presence and technical credibility to work effectively with CTOs, Fellows, senior engineering executives and business leaders. Ability to operate effectively with incomplete information, rapidly changing technology and complex organizational dependencies while still driving decisions and execution. Demonstrated ability to lead through influence across organizations where direct reporting authority does not exist. Track record of attracting, mentoring and developing exceptional senior technical talent. Preferred experience Senior architecture leadership in personal computing, semiconductor, operating-system, AI-platform, cloud/edge or large-scale device organizations. Experience working directly with major silicon, operating-system, AI, memory, cloud and device-ecosystem companies. Experience spanning both technology creation and productization-not solely research, standards or product execution. Experience with multi-platform architectures involving multiple silicon vendors, operating environments and product categories. Experience developing joint reference architectures, co-engineering programs, industry standards or major partner-dependent technology initiatives. Advanced degree in Computer Science, Computer Engineering, Electrical Engineering or a related discipline, or equivalent depth of industry experience. The pay range for this role is $350,000 to $450,000 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Engineering Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status . click apply for full job details
Senior Manager, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Senior Manager, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/12/2026
Full time
Machine Learning Engineer 5 (Senior Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. The Boeing Commercial Airplanes (BCA), 787 Interiors organization is seeking multiple Experienced or SeniorCabin Systems Engineers to join our team in NorthCharleston, SC. At Boeing, we are dedicated to designing and integrating advanced electrical cabin systems to advance the future of our airplane interiors and passenger experience. Our projects focus on translating high-level concepts and requirements into the system design, ensuring the seamless physical integration of electrical systems and components within our aircraft. We collaborate with a global supplier network to implement cutting-edge system hardware and software, validating our designs through rigorous testing. Our engineers work on aircraft systems from initial concept through certification, delivery, and throughout their production lifecycle, continually pushing the boundaries of innovation in commercial air transport. This position will specifically involve working with Cabin Systems, which encompasses interior lighting, passenger address systems, in-flight entertainment, seatback video, passenger connectivity, satellite connections and more. Our teams are currently hiring for a broad range of experience levels including Experienced and Senior Electronic Systems Design and Analysis Engineers. Our team is currently hiring for a broad range of experience levels including Experienced (Level 3) Senior (Level 4) Systems Engineers. Position Responsibilities: Develops and documents complex electronic and electrical system designs. Tests and validates to ensure system designs meet operational and functional requirements Assists in monitoring supplier performance to ensure system integration and compliance with requirements Solves problems concerning fielded hardware and software over the entire product lifecycle Researches specific technology advances for potential application to company business needs Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering (with a focus in Electrical, Mechanical or Aeronautical), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 3+ years of experience with Cabin Systems engineering or equivalent in a related field. Demonstrated design and system thinking skills Preferred Qualifications (Desired Skills/Experience): Level 4: 5+ years of experience with Cabin Systems engineering or equivalent in a related field Experience with Cabin Systems Experience working with suppliers Experience interfacing with E-UMs/the FAA and/or other certification regulatory agencies Exceptional organizational skills with attention to detail. Drug Free Workplace: Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies. Pay Range Summary: At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities. The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements. Please note that the salary information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Summary pay range Experienced Level 3: $112,200 - $151,800 Summary pay range Senior Level 4: $136,850 - $185,150 Applications for this position will be accepted until Nov. 27, 2026 Export Control Requirements: This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. 120.62 is required. "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee. Export Control Details: US based job, US Person required Education Bachelor's Degree or Equivalent Required Relocation This position offers relocation based on candidate eligibility. Visa Sponsorship Employer will not sponsor applicants for employment visa status. Shift This position is for 1st shift Equal Opportunity Employer: Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
11/12/2026
Full time
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. The Boeing Commercial Airplanes (BCA), 787 Interiors organization is seeking multiple Experienced or SeniorCabin Systems Engineers to join our team in NorthCharleston, SC. At Boeing, we are dedicated to designing and integrating advanced electrical cabin systems to advance the future of our airplane interiors and passenger experience. Our projects focus on translating high-level concepts and requirements into the system design, ensuring the seamless physical integration of electrical systems and components within our aircraft. We collaborate with a global supplier network to implement cutting-edge system hardware and software, validating our designs through rigorous testing. Our engineers work on aircraft systems from initial concept through certification, delivery, and throughout their production lifecycle, continually pushing the boundaries of innovation in commercial air transport. This position will specifically involve working with Cabin Systems, which encompasses interior lighting, passenger address systems, in-flight entertainment, seatback video, passenger connectivity, satellite connections and more. Our teams are currently hiring for a broad range of experience levels including Experienced and Senior Electronic Systems Design and Analysis Engineers. Our team is currently hiring for a broad range of experience levels including Experienced (Level 3) Senior (Level 4) Systems Engineers. Position Responsibilities: Develops and documents complex electronic and electrical system designs. Tests and validates to ensure system designs meet operational and functional requirements Assists in monitoring supplier performance to ensure system integration and compliance with requirements Solves problems concerning fielded hardware and software over the entire product lifecycle Researches specific technology advances for potential application to company business needs Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering (with a focus in Electrical, Mechanical or Aeronautical), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 3+ years of experience with Cabin Systems engineering or equivalent in a related field. Demonstrated design and system thinking skills Preferred Qualifications (Desired Skills/Experience): Level 4: 5+ years of experience with Cabin Systems engineering or equivalent in a related field Experience with Cabin Systems Experience working with suppliers Experience interfacing with E-UMs/the FAA and/or other certification regulatory agencies Exceptional organizational skills with attention to detail. Drug Free Workplace: Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies. Pay Range Summary: At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities. The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements. Please note that the salary information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Summary pay range Experienced Level 3: $112,200 - $151,800 Summary pay range Senior Level 4: $136,850 - $185,150 Applications for this position will be accepted until Nov. 27, 2026 Export Control Requirements: This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. 120.62 is required. "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee. Export Control Details: US based job, US Person required Education Bachelor's Degree or Equivalent Required Relocation This position offers relocation based on candidate eligibility. Visa Sponsorship Employer will not sponsor applicants for employment visa status. Shift This position is for 1st shift Equal Opportunity Employer: Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
Job Description Job Description Job Description We are seeking an experienced and highly motivated Senior Application Engineer to join our team focusing on DDR5 solutions. In this role, you will play a critical part in driving the validation, implementation, and optimization of DDR5 memory systems, specifically focusing on digital and power efficiency. You will collaborate with cross-functional teams, to ensure that DDR5 power systems meet the highest standards of quality and reliability. Key Responsibilities: Product Validation : Validation of new products within the power modules for DDR5 memory and memory controllers, ensuring compliance with industry standards and customer requirements. This includes heavy bench measurements to collect data and validate full functionality of new products. System-level Analysis : Conduct analysis of different DDR5 modules to identify performance and develop strategies to enhance system power efficiency without compromising performance. Tool Development : Create and maintain bench automation software for data collection, as well as simulation models and tools to analyze DDR5 power consumption at various system levels (e.g., chip, board, and system). Customer Support : Provide technical support for DDR5 power-related issues during product development and integration phases. Work directly with customers to resolve any technical issues or complex power-related challenges. Collaboration with Cross-functional Teams : Work closely with design, product, test, packaging and other teams to ensure DDR5 solutions meet all performance and specification requirements. Documentation and Reporting : Prepare technical documentation, including specifications, datasheets, power analysis reports, validation reports and test plans to support internal and external stakeholders. Qualifications Education : Bachelor's or Master's degree in Electrical Engineering (or a related field). Experience : 4+ years of experience in power management, memory system design, or related fields (3+ years of focus on DDR5 or similar high-speed memory technologies will be a plus). Skills & Expertise : Hands-on experience with bench validation of analog, digital, and power management devices (such as PMICs, SPD Hub, I3C switches, Temp sensor, etc.) Strong understanding and knowledge of analog and mixed signal circuits (such as amplifiers, temperature sensors, ADC, DAC, voltage regulators, and related power components) Automation experience using LabVIEW, Python or similar programming languages Experience with customer support for technical design and resolving any issues at the application level Experience with developing customer reports, Application notes, datasheets and other technical collateral Communication : Excellent written and verbal communication skills, with the ability to explain complex technical concepts to cross-functional teams and customers. Preferred Qualifications: Advanced Degree : Master's or Ph.D. in Electrical Engineering (or a related field). Additional Experience : Familiarity with DDR5 JEDEC standards and protocols is a plus Expertise in power modeling and simulation tools will be a plus Expertise in hardware design tools will be a plus Additional Information The expected annual pay range for this position is $120K-$145K. This position is also eligible for bonus opportunities. Please note that final offer amount will be dependent on geographic location, applicable experience, and skillset of the candidate. Renesas offers a full range of elective benefits including medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&D, and pet insurance. In addition to elective benefit options, benefited employees receive company-paid life insurance and AD&D, LTD, short term medical benefits as well as paid sick time, paid holidays, and accrued paid vacation. New employees will attend a detailed benefit orientation to learn more about our many benefits and resources Renesas is an embedded semiconductor solution provider driven by its Purpose, To Make Our Lives Easier . With a global team of over 21,000 engineers and problem solvers in more than 30 countries, we offer the opportunity to work on world leading technology for Automotive, Industrial, Infrastructure, and IoT, shaping a safer, healthier, greener, and smarter future. At Renesas, TAGIE is our culture, grounded in being Transparent, Agile, Global, Innovative, and Entrepreneurial. It shapes how we work, grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives. We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process. Are you ready to join our team and shape the future with us? Renesas Electronics is an equal opportunity and affirmative action employer, committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by law. For more information, please read our Diversity & Inclusion Statement. Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.
11/12/2026
Full time
Job Description Job Description Job Description We are seeking an experienced and highly motivated Senior Application Engineer to join our team focusing on DDR5 solutions. In this role, you will play a critical part in driving the validation, implementation, and optimization of DDR5 memory systems, specifically focusing on digital and power efficiency. You will collaborate with cross-functional teams, to ensure that DDR5 power systems meet the highest standards of quality and reliability. Key Responsibilities: Product Validation : Validation of new products within the power modules for DDR5 memory and memory controllers, ensuring compliance with industry standards and customer requirements. This includes heavy bench measurements to collect data and validate full functionality of new products. System-level Analysis : Conduct analysis of different DDR5 modules to identify performance and develop strategies to enhance system power efficiency without compromising performance. Tool Development : Create and maintain bench automation software for data collection, as well as simulation models and tools to analyze DDR5 power consumption at various system levels (e.g., chip, board, and system). Customer Support : Provide technical support for DDR5 power-related issues during product development and integration phases. Work directly with customers to resolve any technical issues or complex power-related challenges. Collaboration with Cross-functional Teams : Work closely with design, product, test, packaging and other teams to ensure DDR5 solutions meet all performance and specification requirements. Documentation and Reporting : Prepare technical documentation, including specifications, datasheets, power analysis reports, validation reports and test plans to support internal and external stakeholders. Qualifications Education : Bachelor's or Master's degree in Electrical Engineering (or a related field). Experience : 4+ years of experience in power management, memory system design, or related fields (3+ years of focus on DDR5 or similar high-speed memory technologies will be a plus). Skills & Expertise : Hands-on experience with bench validation of analog, digital, and power management devices (such as PMICs, SPD Hub, I3C switches, Temp sensor, etc.) Strong understanding and knowledge of analog and mixed signal circuits (such as amplifiers, temperature sensors, ADC, DAC, voltage regulators, and related power components) Automation experience using LabVIEW, Python or similar programming languages Experience with customer support for technical design and resolving any issues at the application level Experience with developing customer reports, Application notes, datasheets and other technical collateral Communication : Excellent written and verbal communication skills, with the ability to explain complex technical concepts to cross-functional teams and customers. Preferred Qualifications: Advanced Degree : Master's or Ph.D. in Electrical Engineering (or a related field). Additional Experience : Familiarity with DDR5 JEDEC standards and protocols is a plus Expertise in power modeling and simulation tools will be a plus Expertise in hardware design tools will be a plus Additional Information The expected annual pay range for this position is $120K-$145K. This position is also eligible for bonus opportunities. Please note that final offer amount will be dependent on geographic location, applicable experience, and skillset of the candidate. Renesas offers a full range of elective benefits including medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&D, and pet insurance. In addition to elective benefit options, benefited employees receive company-paid life insurance and AD&D, LTD, short term medical benefits as well as paid sick time, paid holidays, and accrued paid vacation. New employees will attend a detailed benefit orientation to learn more about our many benefits and resources Renesas is an embedded semiconductor solution provider driven by its Purpose, To Make Our Lives Easier . With a global team of over 21,000 engineers and problem solvers in more than 30 countries, we offer the opportunity to work on world leading technology for Automotive, Industrial, Infrastructure, and IoT, shaping a safer, healthier, greener, and smarter future. At Renesas, TAGIE is our culture, grounded in being Transparent, Agile, Global, Innovative, and Entrepreneurial. It shapes how we work, grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives. We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process. Are you ready to join our team and shape the future with us? Renesas Electronics is an equal opportunity and affirmative action employer, committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by law. For more information, please read our Diversity & Inclusion Statement. Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Job Description Date Posted: 2026-07-14 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 801 (External Site) Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon is seeking a Senior Systems Security Engineer - Anti-Tamper/Program Protection (P3) to join our elite Systems Security Engineering (SSE) team within the Systems Engineering and Test Capabilities Directorate. This role is critical to safeguarding our Warfighters' technological advantages through the creation and integration of holistic security solutions, including Anti-Tamper, Cyber Security, Software Assurance and Supply Chain Risk Management. Join us in developing solutions that protect our nation and directly contribute to delivering for all those who defend all of us. This is an onsite position at Raytheon in Tucson, AZ. What You Will Do Support the implementation of Systems Security Engineering (SSE) solutions in Raytheon products Interact with customers to define SSE requirements, solutions, trades, costs, and implementation strategies Develop plans, estimates, task execution schedules, and risk mitigation strategies Guide SSE implementations and architectures for customer systems Conduct attack threat modeling and Critical Program Information (CPI) assessments Develop top-level system requirements and flow those into subsystem implementation concepts Ensure compliance with DoD technology release and export licensing policies Consult and assist program management with SSE architecture and issues Qualifications You Must Have Typically requires a Bachelor's Degree in Science, Technology, Engineering or Mathematics (STEM) and 5 years of prior relevant experience The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Experience in System Security Engineering, Anti-Tamper, Cybersecurity or Embedded System Security Experience in designing, implementing, testing and fielding real-time embedded security solutions for DoD programs Experience generating systems requirements, design and architecture artifacts, plans and/or policies Qualifications We Prefer Active and transferable U.S. government issued DoD Secret security clearance Advanced Degree in Electrical Engineering, Systems Engineering, Mechanical Engineering, Computer Science or related fields Experience in developing Anti-Tamper, Cyber Security, and/or Program Protection requirements, architectures and plans Familiarity with software, firmware, microelectronics engineering, cryptography and FPGA design Expertise in attack threat modeling and Critical Program Information (CPI) assessments Cybersecurity certifications such as CISSP, GSLC or CEH in accordance with DoDD 8570/8140 Working knowledge of DoD directives such as DODI-S-5230.28 Experience in aircraft/weapons system integration Exceptional creativity, problem-solving abilities, and strong interpersonal skills What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligible - Relocation assistance is available Learn More & Apply Now! Please consider the following role type definition as you apply for this role. Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. This position requires onsite work in Tucson, AZ: -tucson,-az-location Location Information This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links: "Raytheon In Tucson": -tucson,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
