Job Description Job Description Primary Responsibilities Design, build, and support Continuous Integration/Continuous Delivery (CI/CD) automation pipelines using secure code practices. Work well with Architects, Lead Engineers, Product Owners and Product Managers to craft the right DevSecOps solutions to deliver business applications in the cloud. Seek out opportunities to develop and improve the existing automation pipelines and processes. Automate the secure provisioning, setup, maintenance of environments including servers, resources, and databases in the cloud (AWS) as well as on-prem across Dev/Test/Production environments. Participate in Kanban/Scrum based Agile teams focused on business unit success. The Expertise and Skills You Bring A minimum of 10 years of experience in a Software Engineering function with at least 5 of those in a hands-on DevOps role. Strong experience working with modern infrastructure technologies such as containerization, Automation, and build pipelines in Amazon AWS and/or Microsoft Azure Strong experience with Continuous Integration and Continuous Delivery using tools like Concourse, GIT, Jenkins, Artifactory, Veracode, and uDeploy. Experience with automated application build and support using Maven/Gradle/Ant or other tools. Knowledge of configuration management and infrastructure management systems like Ansible, Chef, Docker, Kubernetes, CloudFormation, EKS. Experience with supervising systems such as CloudWatch, Datadog/Splunk, ELK stack Good knowledge of open source platforms (Apache, Tomcat, NodeJS etc.) Basic understanding of design and development of modern service based applications with Front-end (Angular, React, HTML, JavaScript, CSS) and RESTful Back end (NodeJS, Java 8 , Spring) Experience with Automation including Unit, and Integration Testing Design, implement, customize, deploy and maintain CICD pipelines and configuration management. Migrating on-premises applications to public cloud platforms like AWS, AZURE, GCP, Openstack. And evaluating new tools to improve build and release processes. Working with AWS services like EC2, S3, RDS, Lambda, Athena Writing Cloud Formation Templates, Terraform, Ansible modules. Using python/boto/any languages for implementing AWS solutions Supervise the health of production and test environments, experience with SRE, Observability, monitoring. Troubleshoot and debug build Issues, with a willingness to resolve problems. Collect and report on operational metrics for SLA reporting and capacity planning. Strong grasp of Unix-based operating processing systems (Linux). Bachelor's degree in a technical field such as computer science/engineering or related field AWS certification (Solution Architect/DevOps) required. Experience of working within an Agile environment
10/31/2026
Full time
Job Description Job Description Primary Responsibilities Design, build, and support Continuous Integration/Continuous Delivery (CI/CD) automation pipelines using secure code practices. Work well with Architects, Lead Engineers, Product Owners and Product Managers to craft the right DevSecOps solutions to deliver business applications in the cloud. Seek out opportunities to develop and improve the existing automation pipelines and processes. Automate the secure provisioning, setup, maintenance of environments including servers, resources, and databases in the cloud (AWS) as well as on-prem across Dev/Test/Production environments. Participate in Kanban/Scrum based Agile teams focused on business unit success. The Expertise and Skills You Bring A minimum of 10 years of experience in a Software Engineering function with at least 5 of those in a hands-on DevOps role. Strong experience working with modern infrastructure technologies such as containerization, Automation, and build pipelines in Amazon AWS and/or Microsoft Azure Strong experience with Continuous Integration and Continuous Delivery using tools like Concourse, GIT, Jenkins, Artifactory, Veracode, and uDeploy. Experience with automated application build and support using Maven/Gradle/Ant or other tools. Knowledge of configuration management and infrastructure management systems like Ansible, Chef, Docker, Kubernetes, CloudFormation, EKS. Experience with supervising systems such as CloudWatch, Datadog/Splunk, ELK stack Good knowledge of open source platforms (Apache, Tomcat, NodeJS etc.) Basic understanding of design and development of modern service based applications with Front-end (Angular, React, HTML, JavaScript, CSS) and RESTful Back end (NodeJS, Java 8 , Spring) Experience with Automation including Unit, and Integration Testing Design, implement, customize, deploy and maintain CICD pipelines and configuration management. Migrating on-premises applications to public cloud platforms like AWS, AZURE, GCP, Openstack. And evaluating new tools to improve build and release processes. Working with AWS services like EC2, S3, RDS, Lambda, Athena Writing Cloud Formation Templates, Terraform, Ansible modules. Using python/boto/any languages for implementing AWS solutions Supervise the health of production and test environments, experience with SRE, Observability, monitoring. Troubleshoot and debug build Issues, with a willingness to resolve problems. Collect and report on operational metrics for SLA reporting and capacity planning. Strong grasp of Unix-based operating processing systems (Linux). Bachelor's degree in a technical field such as computer science/engineering or related field AWS certification (Solution Architect/DevOps) required. Experience of working within an Agile environment
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: SCI TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work - and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. We have an opening for an Embedded Software Engineer Level 3 or 4 to join our team of qualified, diverse individuals in the Space Systems organization developing space flight software platforms for National Space Security programs. The individual we seek will be self-motivated, proactive, and goal-oriented. This position will be in Dulles, VA. This work does require a TS/SCI clearance and will primarily be performed in a SCIF environment. In this role you will: Develop embedded software modules that can interact directly with hardware protocols and interfaces including UART, Synchronous Serial, MIL-STD-1553, SPACEWIRE, SPI, discrete digital and analog IO. Work with other disciplines to establish Flight-Software requirements, testing and verification plan. Develop and configure board support packages (BSPs) and integrate device drivers. Performs trade studies via computer simulation or kits & development boards. Work with multiple engineers to integrate spacecraft components and flight software with the simulation platform. Be involved in the hardware definition and software design, development, debug and integration on simulation and hardware-in-the-loop platforms. Analyze system resources to enhance efficiency, stability, and processing speed. Prepare design documentation, analysis, test results and presentation materials for internal and external customers. Work with software developers and other engineers, as needed, to help diagnose and identify the root cause of problems found during software installation, integration, acceptance test, and operational events. Work in an innovative environment across diverse assignments and in collaborative team settings across all levels. This position will work a 9/80 schedule, with every other Friday off. This position is 100% onsite and cannot accommodate telecommute work. This position is contingent upon the candidate obtaining final clearances and program access(es) within a reasonable period of time as determined by the company. This position can be filled as a Principal (level 3) or Sr Principal (level 4) depending on experience and qualifications Basic Qualifications for Level 3: Bachelor's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 5 years of relevant professional experience - OR - Master's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 3 years of relevant professional experience - OR - PhD in Aerospace/Electrical/Computer/Software Engineering or related STEM field Requires an active U.S. Government Top-Secret TS security clearance and Sensitive Compartmented Information (SCI) TS/SCI at time of application, current and within scope, with the ability to obtain and maintain Special Access Program (SAP) approval/access within a reasonable amount of time US citizenship required Advanced programming proficiency with: C/C++, Python. Advanced programming proficiency with Matlab. Excellent communication skills and ability to work in small teams. Ability to debug hardware and software. Ability to use software revision control tools such as Subversion and Git. Ability to clearly document technical and programmatic status to management. Basic Qualifications for Level 4: Bachelor's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 8 years of relevant professional experience - OR - Master's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 6 years of relevant professional experience - OR - PhD in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 4 years of relevant professional experience. Requires an active U.S. Government Top-Secret TS security clearance and Sensitive Compartmented Information (SCI) TS/SCI at time of application, current and within scope, with the ability to obtain and maintain Special Access Program (SAP) approval/access within a reasonable amount of time US citizenship required Advanced programming proficiency with: C/C++, Python. Advanced programming proficiency with Matlab. Excellent communication skills and ability to work in small teams. Ability to debug hardware and software. Ability to use software revision control tools such as Subversion and Git. Ability to clearly document technical and programmatic status to management. Preferred Qualifications: Active TS/SCI clearance with SAP System knowledge in one or more of the following domains: Spacecraft Command & Control, Mission Planning, Space Situational Awareness and Visualization Familiarity with static code analysis tools such as: Coverity, SonarQube, and Fortify. Hardware interfacing, integration and test and controls experience Understanding of common embedded system tools, real-time operating systems and avionics integration and test practices Ability to integrate Flight-Software using simulation models of sensors, actuators and space environments to demonstrate closed-loop spacecraft system performance, general integration and test of aerospace systems. Understanding of Jenkins, Jira (Agile, Scrum and Kanban), Bitbucket and related DevSecOps tools. Excellent communication, interpersonal skills, and the ability to interface with all levels of employees and management Experience developing software in a Linux OS environment Experience with National Instruments data acquisition cards. Ability to read schematics, and work with components datasheets. Experience with Digital, Analog, RS-422 synchronous serial and UART, MIL-STD-1553, SpaceWire electrical interfaces Primary Level Salary Range: $114,000.00 - $171,000.00 Secondary Level Salary Range: $142,200.00 - $213,400.00 The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business. The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
10/31/2026
Full time
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: SCI TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work - and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. We have an opening for an Embedded Software Engineer Level 3 or 4 to join our team of qualified, diverse individuals in the Space Systems organization developing space flight software platforms for National Space Security programs. The individual we seek will be self-motivated, proactive, and goal-oriented. This position will be in Dulles, VA. This work does require a TS/SCI clearance and will primarily be performed in a SCIF environment. In this role you will: Develop embedded software modules that can interact directly with hardware protocols and interfaces including UART, Synchronous Serial, MIL-STD-1553, SPACEWIRE, SPI, discrete digital and analog IO. Work with other disciplines to establish Flight-Software requirements, testing and verification plan. Develop and configure board support packages (BSPs) and integrate device drivers. Performs trade studies via computer simulation or kits & development boards. Work with multiple engineers to integrate spacecraft components and flight software with the simulation platform. Be involved in the hardware definition and software design, development, debug and integration on simulation and hardware-in-the-loop platforms. Analyze system resources to enhance efficiency, stability, and processing speed. Prepare design documentation, analysis, test results and presentation materials for internal and external customers. Work with software developers and other engineers, as needed, to help diagnose and identify the root cause of problems found during software installation, integration, acceptance test, and operational events. Work in an innovative environment across diverse assignments and in collaborative team settings across all levels. This position will work a 9/80 schedule, with every other Friday off. This position is 100% onsite and cannot accommodate telecommute work. This position is contingent upon the candidate obtaining final clearances and program access(es) within a reasonable period of time as determined by the company. This position can be filled as a Principal (level 3) or Sr Principal (level 4) depending on experience and qualifications Basic Qualifications for Level 3: Bachelor's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 5 years of relevant professional experience - OR - Master's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 3 years of relevant professional experience - OR - PhD in Aerospace/Electrical/Computer/Software Engineering or related STEM field Requires an active U.S. Government Top-Secret TS security clearance and Sensitive Compartmented Information (SCI) TS/SCI at time of application, current and within scope, with the ability to obtain and maintain Special Access Program (SAP) approval/access within a reasonable amount of time US citizenship required Advanced programming proficiency with: C/C++, Python. Advanced programming proficiency with Matlab. Excellent communication skills and ability to work in small teams. Ability to debug hardware and software. Ability to use software revision control tools such as Subversion and Git. Ability to clearly document technical and programmatic status to management. Basic Qualifications for Level 4: Bachelor's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 8 years of relevant professional experience - OR - Master's degree in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 6 years of relevant professional experience - OR - PhD in Aerospace/Electrical/Computer/Software Engineering or related STEM field with 4 years of relevant professional experience. Requires an active U.S. Government Top-Secret TS security clearance and Sensitive Compartmented Information (SCI) TS/SCI at time of application, current and within scope, with the ability to obtain and maintain Special Access Program (SAP) approval/access within a reasonable amount of time US citizenship required Advanced programming proficiency with: C/C++, Python. Advanced programming proficiency with Matlab. Excellent communication skills and ability to work in small teams. Ability to debug hardware and software. Ability to use software revision control tools such as Subversion and Git. Ability to clearly document technical and programmatic status to management. Preferred Qualifications: Active TS/SCI clearance with SAP System knowledge in one or more of the following domains: Spacecraft Command & Control, Mission Planning, Space Situational Awareness and Visualization Familiarity with static code analysis tools such as: Coverity, SonarQube, and Fortify. Hardware interfacing, integration and test and controls experience Understanding of common embedded system tools, real-time operating systems and avionics integration and test practices Ability to integrate Flight-Software using simulation models of sensors, actuators and space environments to demonstrate closed-loop spacecraft system performance, general integration and test of aerospace systems. Understanding of Jenkins, Jira (Agile, Scrum and Kanban), Bitbucket and related DevSecOps tools. Excellent communication, interpersonal skills, and the ability to interface with all levels of employees and management Experience developing software in a Linux OS environment Experience with National Instruments data acquisition cards. Ability to read schematics, and work with components datasheets. Experience with Digital, Analog, RS-422 synchronous serial and UART, MIL-STD-1553, SpaceWire electrical interfaces Primary Level Salary Range: $114,000.00 - $171,000.00 Secondary Level Salary Range: $142,200.00 - $213,400.00 The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business. The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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).
10/31/2026
Full time
Machine Learning Engineer 4 - Machine Learning Foundations (MLX) 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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).
10/31/2026
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).
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) 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. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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).
10/31/2026
Full time
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) 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. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 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 4 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Philadelphia, PA: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 Wilmington, DE: $179,400 - $204,700 for Machine Learning Engineer 4 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).
10/31/2026
Full time
Machine Learning Engineer 4 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Philadelphia, PA: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 Wilmington, DE: $179,400 - $204,700 for Machine Learning Engineer 4 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).
10/31/2026
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).
Machine Learning Engineer 4 (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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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. Chicago, IL: $179,400 - $204,700 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 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).
10/31/2026
Full time
Machine Learning Engineer 4 (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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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. Chicago, IL: $179,400 - $204,700 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 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 4 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Philadelphia, PA: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 Wilmington, DE: $179,400 - $204,700 for Machine Learning Engineer 4 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).
10/31/2026
Full time
Machine Learning Engineer 4 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 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 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 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 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ 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. 3+ 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) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). 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: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Philadelphia, PA: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 Wilmington, DE: $179,400 - $204,700 for Machine Learning Engineer 4 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 Job Description Why Etherealize? Etherealize is building the rails to bring Wall Street into the 21st century. Today's financial infrastructure wastes billions in trapped capital and operational inefficiency, forcing institutions to maintain massive reserves, limiting market liquidity, and creating systemic risk that grows more dangerous as markets become increasingly global and interconnected. With $40M in funding from Electric Capital and Paradigm, we are bringing together the best minds from Ethereum and Wall Street to rebuild the infrastructure that underpins the financial system - faster, safer, fully on-chain. We are looking for a Senior DevOps Engineer to own how everything we build gets deployed, secured, observed and kept running. You will be joining a team dedicated to unlocking the true potential of on-chain finance, creating a world where traditional assets flow seamlessly through blockchain protocols. Etherealize has a series of products moving from beta to production with institutional clients, and we need the right person to make sure they run flawlessly. Why This Role Exists Until now, infrastructure and deployments for our web application have been handled by the engineering team alongside their product work. As we move from beta into production, with multiple client environments, contractual SLAs and SOC 2 on the horizon, that is no longer sustainable. At the same time, our blockchain infrastructure , including an Ethereum execution client instance we operate ourselves and a ZK proving pipeline running alongside it, is about to become a first-class production concern. This is not a backfill. You will be the first dedicated DevOps hire and the foremost infrastructure expert in the company. The basics are in place; you will reimagine our deployments, monitoring, alerting, runbooks and infrastructure security for production, and own them end to end. What Will You Do? You will sit across engineering, security and the protocol team, and will be expected to look at an architecture diagram and know how you want to deploy it and keep it running - we will be asking you what we should do, not the other way around. Infrastructure as Code: Own our AWS infrastructure in Terraform. Design modular, well-architected Terraform that scales cleanly across multiple client environments and maintain it with the attention to detail that production financial infrastructure demands; a single misconfigured variable or secret is a latent bug a client will find later. Web Application Operations: Take over deployment and management of our client-facing web application environments, including CI/CD, environment provisioning and regular contract and application upgrades. Blockchain Node Operations: Run and maintain Ethereum node software in production including Ethereum L1 nodes and Reth-based execution client instances where we are the sole operator of the state. Keep them in sync, snapshot and restore them, run read replicas, handle reorgs, and know what to watch for before it becomes a problem. ZK Proving Infrastructure: Operate the proving pipeline that runs alongside our execution client, including managing and monitoring a GPU cluster. You do not need to understand the cryptography; you do need to keep a heterogeneous, GPU-heavy workload healthy, scalable and observable. Site Reliability & Observability: Build the monitoring, dashboards and alerting we will need to demonstrate uptime against client SLAs for both conventional web metrics and chain-specific health (sync distance, block times, time since last block, proving throughput). Design and test backups, disaster recovery, multi-AZ and multi-region resilience, and traffic failover. DevSecOps & Secrets Management: Bring secrets management into the infrastructure-as-code pipeline (HashiCorp Vault or equivalent), including private key and signer key handling, and partner with our security lead on SOC 2 readiness, policy-as-code and infrastructure controls. Incident Response & Runbooks: Define how the company handles incidents in production: on-call, escalation, runbooks and post-mortems. Cross-team Partnership: Work closely with the protocol engineers who built our execution client customisations and proving pipeline to understand how the services fit together and iterate on how they are deployed and operated. Who Are You? You are a hands-on senior operator who wants a blank slate and the autonomy to build it right, and who is comfortable executing as a one- or two-person function rather than hiring a department. Required 5+ years in DevOps, platform engineering or SRE roles, with at least 3 years writing and managing production-grade Terraform on AWS. You build modular, reusable Terraform, and if we handed you an environment whose state file had drifted badly out of sync and asked you to reconcile it without taking anything down, you would smile and say "that's easy." Front-line experience deploying and operating production infrastructure at serious companies, where uptime and data integrity had real business consequences. Strong SRE fundamentals: observability, alerting, backups and restores, disaster recovery, high availability across zones and regions. Secrets management in an infrastructure-as-code pipeline (HashiCorp Vault or equivalent), including signing keys held in a hardware or cryptographic boundary (e.g., cloud KMS, HSM, MPC, or Vault Transit) with rotation and access control. Genuine blockchain familiarity. You have worked with Ethereum or EVM infrastructure and understand what a node does, how it syncs and what can go wrong. Meticulous attention to detail, strong communication, and the raw problem-solving ability to get into genuinely hard, novel infrastructure problems. Strongly Preferred Hands-on experience running Ethereum L1 or L2 node software in production (e.g. at a node provider, staking operator, L2 team or exchange): snapshots, restores, read replicas, reorg handling, sync monitoring. Experience operating a Reth instance or an L2 / rollup stack. Deeper HashiCorp ecosystem experience: Sentinel (policy as code), Boundary. SOC 2 or comparable compliance experience from the infrastructure side. Nice to Have Operating ZK proving infrastructure or GPU clusters (monitoring, scaling, hardware health). Integrating with Web3 custodians and the key-management, network and data-centre security requirements that come with them. Kubernetes, and container-based deployment at scale. What's In It For You? Front-row seat to Ethereum history: You will own the infrastructure of a company fundamentally changing how financial markets operate, in a flexible, fast-moving environment where your impact is immediately visible. Scope & autonomy: You will define how Etherealize does infrastructure, security operations and reliability from the ground up, and have the ear of engineering, security and leadership while you do it. Career rocket fuel: We are one of the most dynamic and exciting startups in Ethereum, with deep ties to the Ethereum Foundation and other foundational Ethereum institutions. You'll work directly with Zach Obront (CTO, secured $10B+ in on-chain assets, ZK & L2 systems), alongside co-founder Danny Ryan (led Ethereum's Merge) and a team from Coinbase, Bloomberg, Microsoft, and Kraken. After this role, the sky's the limit for your career.
10/31/2026
Full time
Job Description Job Description Why Etherealize? Etherealize is building the rails to bring Wall Street into the 21st century. Today's financial infrastructure wastes billions in trapped capital and operational inefficiency, forcing institutions to maintain massive reserves, limiting market liquidity, and creating systemic risk that grows more dangerous as markets become increasingly global and interconnected. With $40M in funding from Electric Capital and Paradigm, we are bringing together the best minds from Ethereum and Wall Street to rebuild the infrastructure that underpins the financial system - faster, safer, fully on-chain. We are looking for a Senior DevOps Engineer to own how everything we build gets deployed, secured, observed and kept running. You will be joining a team dedicated to unlocking the true potential of on-chain finance, creating a world where traditional assets flow seamlessly through blockchain protocols. Etherealize has a series of products moving from beta to production with institutional clients, and we need the right person to make sure they run flawlessly. Why This Role Exists Until now, infrastructure and deployments for our web application have been handled by the engineering team alongside their product work. As we move from beta into production, with multiple client environments, contractual SLAs and SOC 2 on the horizon, that is no longer sustainable. At the same time, our blockchain infrastructure , including an Ethereum execution client instance we operate ourselves and a ZK proving pipeline running alongside it, is about to become a first-class production concern. This is not a backfill. You will be the first dedicated DevOps hire and the foremost infrastructure expert in the company. The basics are in place; you will reimagine our deployments, monitoring, alerting, runbooks and infrastructure security for production, and own them end to end. What Will You Do? You will sit across engineering, security and the protocol team, and will be expected to look at an architecture diagram and know how you want to deploy it and keep it running - we will be asking you what we should do, not the other way around. Infrastructure as Code: Own our AWS infrastructure in Terraform. Design modular, well-architected Terraform that scales cleanly across multiple client environments and maintain it with the attention to detail that production financial infrastructure demands; a single misconfigured variable or secret is a latent bug a client will find later. Web Application Operations: Take over deployment and management of our client-facing web application environments, including CI/CD, environment provisioning and regular contract and application upgrades. Blockchain Node Operations: Run and maintain Ethereum node software in production including Ethereum L1 nodes and Reth-based execution client instances where we are the sole operator of the state. Keep them in sync, snapshot and restore them, run read replicas, handle reorgs, and know what to watch for before it becomes a problem. ZK Proving Infrastructure: Operate the proving pipeline that runs alongside our execution client, including managing and monitoring a GPU cluster. You do not need to understand the cryptography; you do need to keep a heterogeneous, GPU-heavy workload healthy, scalable and observable. Site Reliability & Observability: Build the monitoring, dashboards and alerting we will need to demonstrate uptime against client SLAs for both conventional web metrics and chain-specific health (sync distance, block times, time since last block, proving throughput). Design and test backups, disaster recovery, multi-AZ and multi-region resilience, and traffic failover. DevSecOps & Secrets Management: Bring secrets management into the infrastructure-as-code pipeline (HashiCorp Vault or equivalent), including private key and signer key handling, and partner with our security lead on SOC 2 readiness, policy-as-code and infrastructure controls. Incident Response & Runbooks: Define how the company handles incidents in production: on-call, escalation, runbooks and post-mortems. Cross-team Partnership: Work closely with the protocol engineers who built our execution client customisations and proving pipeline to understand how the services fit together and iterate on how they are deployed and operated. Who Are You? You are a hands-on senior operator who wants a blank slate and the autonomy to build it right, and who is comfortable executing as a one- or two-person function rather than hiring a department. Required 5+ years in DevOps, platform engineering or SRE roles, with at least 3 years writing and managing production-grade Terraform on AWS. You build modular, reusable Terraform, and if we handed you an environment whose state file had drifted badly out of sync and asked you to reconcile it without taking anything down, you would smile and say "that's easy." Front-line experience deploying and operating production infrastructure at serious companies, where uptime and data integrity had real business consequences. Strong SRE fundamentals: observability, alerting, backups and restores, disaster recovery, high availability across zones and regions. Secrets management in an infrastructure-as-code pipeline (HashiCorp Vault or equivalent), including signing keys held in a hardware or cryptographic boundary (e.g., cloud KMS, HSM, MPC, or Vault Transit) with rotation and access control. Genuine blockchain familiarity. You have worked with Ethereum or EVM infrastructure and understand what a node does, how it syncs and what can go wrong. Meticulous attention to detail, strong communication, and the raw problem-solving ability to get into genuinely hard, novel infrastructure problems. Strongly Preferred Hands-on experience running Ethereum L1 or L2 node software in production (e.g. at a node provider, staking operator, L2 team or exchange): snapshots, restores, read replicas, reorg handling, sync monitoring. Experience operating a Reth instance or an L2 / rollup stack. Deeper HashiCorp ecosystem experience: Sentinel (policy as code), Boundary. SOC 2 or comparable compliance experience from the infrastructure side. Nice to Have Operating ZK proving infrastructure or GPU clusters (monitoring, scaling, hardware health). Integrating with Web3 custodians and the key-management, network and data-centre security requirements that come with them. Kubernetes, and container-based deployment at scale. What's In It For You? Front-row seat to Ethereum history: You will own the infrastructure of a company fundamentally changing how financial markets operate, in a flexible, fast-moving environment where your impact is immediately visible. Scope & autonomy: You will define how Etherealize does infrastructure, security operations and reliability from the ground up, and have the ear of engineering, security and leadership while you do it. Career rocket fuel: We are one of the most dynamic and exciting startups in Ethereum, with deep ties to the Ethereum Foundation and other foundational Ethereum institutions. You'll work directly with Zach Obront (CTO, secured $10B+ in on-chain assets, ZK & L2 systems), alongside co-founder Danny Ryan (led Ethereum's Merge) and a team from Coinbase, Bloomberg, Microsoft, and Kraken. After this role, the sky's the limit for your career.
Adaptive Financial Consulting Ltd
New York, New York
This job is with Adaptive Financial Consulting Ltd, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. WE ARE: At Adaptive, we are a technology provider firm that partners with capital, commodity, and digital market participants to build custom front-office technology, messaging systems, and trading infrastructure. Our experienced teams design and deliver complex front-office technology solutions using our proven accelerators to create long-term competitive advantage. Our clients include the world's leading investment banks, investment managers, fintechs and capital market service providers. With a global reach, with offices in London, New York, Barcelona, Montreal, and Manila, we have a proven track record of delivering powerful, elegant and intuitive trading technology solutions, and we value technical pragmatism, collaboration, and clear communication. We're looking for a Senior Java / Systems Engineer with significant experience in Platform Exchange Systems to design, deliver, and optimize production-ready, high-performance, low-latency technology using Aeron. YOU ARE: A hands-on engineer who enjoys designing and optimising low-latency Java services and protocols across the full delivery lifecycle. Someone with genuine experience building Matching Engines and Platform Exchange Systems. Driven by evidence-based engineering, automated testing, benchmarking, and profiling rather than guesswork. A clear, confident communicator who can work across domain boundaries in a collaborative Agile environment, rather than being siloed into a single technology stack. YOU HAVE: Strong server-side, low-latency Java expertise (concurrency, memory management, I/O, and performance profiling). Solid exchange, risk, or matching-engine experience. Hands-on experience building automated testing strategies, running performance benchmarks, and diagnosing production issues. Excellent technical communication and collaborative problem-solving skills. Experience with order entry and market data protocols (e.g. FIX, ITCH). Familiarity with low-latency frameworks such as Aeron, Chronicle, or LBM. An understanding of replicated state machines, event sourcing, or deterministic systems. Exposure to cloud environments (AWS/GCP), containers, Kubernetes, or observability tooling. YOU WILL: Design, build, and optimise low-latency Java services and protocols for an Exchange Accelerator product across the delivery lifecycle. Define order, session, instrument, and account models alongside exchange integration boundaries. Develop automated testing strategies and perform evidence-based performance benchmarking and profiling. Collaborate directly with client teams, SREs, QA, and leadership to ensure exchange readiness and durable production fixes. Engage with client engineering and business stakeholders, communicating technical trade-offs clearly. Support the product in production across multiple client deployments. (And after six months) Independently own key technical workstreams from concept to production readiness. Deliver maintainable, observable, and well-tested systems aligned with core architecture. Establish trusted relationships with clients through clear communication and steady delivery. WHY US: To be immersed in high-standard engineering culture. Our fantastic team takes pride in crafting complex technical solutions but also loves sharing their knowledge and helping you grow professionally (we have extraordinary minds at Adaptive, you can learn from anyone here, which is the beauty of it). To take part in the growth and development of a great company. Our teams feel free to speak up, make suggestions and raise concerns. Collaborative team environment: we all work together, respect each other, and pitch in Great consideration for work/life balance (highly-flexible, hybrid working model, well-being benefits ). The balance between professional and personal life is massively important to us. We work hard to provide a positive, collaborative and inclusive culture and to positively impact our staff and local communities through different well-being, diversity and inclusion programmes. WHAT PEOPLE THINK OF US You can check our Glassdoor page BENEFITS (What we offer in return what you'll get ): For permanents: We create benefits with YOU in mind. We create benefits with YOU in mind: Flexible hybrid working model Medical from the 1st of the following month of your start date (i.e. if you join on the 24th of July, it starts on the 1st of August). We have 6 Aetna plans to choose from as provided by our PEO, Justworks. We make a flat monthly contribution to your healthcare costs Dental and vision from the 1st of the month following your start date - we have 3 dental and 2 vision plans to choose from. We make fixed contributions to each 23 days of vacation per calendar year plus 11 public holidays Group disability insurance: short-term and long-term (60% and taxable) 401K safe harbor plan where we match contributions up to 5% of base pay on a paycheck-to-paycheck basis (you can opt-in after 90 days of service) Gym subsidy of up to $50 per month (and we pay the taxes on that so it's a real $50) post probation Life insurance at 2 x salary Commuter benefits Health Savings Account and Flexible Spending Account Mental Health First Aiders THE PROCESS Long interview processes are stressful and boring and that is not us! We want to make sure that everything runs smoothly. So here you will have three-stage interviews: 1- A chat with one of our great recruiters. 2- A Zoom chat with one of our Java colleagues where they will ask you detailed questions about your experience. 3- A Face to Face interview (either in our office or via Zoom). During this interview, we will dig even deeper and you will have a pair programming task to do. But don't worry; everything will be explained to you step by step by your recruiter. A little tip for you during those stages: Collaboration is massively important to us, so don't hesitate to share your thoughts, ask questions, ask for help if needed, etc DIVERSITY & INCLUSION: Diversity and inclusion are key to a great workplace, and Adaptive is better when it's more representative of the world around us. We want everyone to feel comfortable bringing their whole selves to work without any fear of judgment or negativity. All we ask is that our colleagues are respectful, collaborative, passionate about what they do, and have the skills needed to be successful in their roles. Background check: the employment/engagement is subject to an acceptable background check that will be run by Adaptive. E-verify: Adaptive Financial Consulting Inc. makes use of E-Verify to validate someone's right to work in the US. We will provide the Social Security Administration, and, if necessary, the Department of Homeland Security, with information from each new employee's Form I-9 to confirm work authorization. Please note that we do not use this information to pre-screen job applicants. Base pay will be determined on an individualized basis and is only part of the total compensation package. Pay is based on candidate skills and experience.New York pay range$240,000-$260,000 USD
10/31/2026
Full time
This job is with Adaptive Financial Consulting Ltd, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. WE ARE: At Adaptive, we are a technology provider firm that partners with capital, commodity, and digital market participants to build custom front-office technology, messaging systems, and trading infrastructure. Our experienced teams design and deliver complex front-office technology solutions using our proven accelerators to create long-term competitive advantage. Our clients include the world's leading investment banks, investment managers, fintechs and capital market service providers. With a global reach, with offices in London, New York, Barcelona, Montreal, and Manila, we have a proven track record of delivering powerful, elegant and intuitive trading technology solutions, and we value technical pragmatism, collaboration, and clear communication. We're looking for a Senior Java / Systems Engineer with significant experience in Platform Exchange Systems to design, deliver, and optimize production-ready, high-performance, low-latency technology using Aeron. YOU ARE: A hands-on engineer who enjoys designing and optimising low-latency Java services and protocols across the full delivery lifecycle. Someone with genuine experience building Matching Engines and Platform Exchange Systems. Driven by evidence-based engineering, automated testing, benchmarking, and profiling rather than guesswork. A clear, confident communicator who can work across domain boundaries in a collaborative Agile environment, rather than being siloed into a single technology stack. YOU HAVE: Strong server-side, low-latency Java expertise (concurrency, memory management, I/O, and performance profiling). Solid exchange, risk, or matching-engine experience. Hands-on experience building automated testing strategies, running performance benchmarks, and diagnosing production issues. Excellent technical communication and collaborative problem-solving skills. Experience with order entry and market data protocols (e.g. FIX, ITCH). Familiarity with low-latency frameworks such as Aeron, Chronicle, or LBM. An understanding of replicated state machines, event sourcing, or deterministic systems. Exposure to cloud environments (AWS/GCP), containers, Kubernetes, or observability tooling. YOU WILL: Design, build, and optimise low-latency Java services and protocols for an Exchange Accelerator product across the delivery lifecycle. Define order, session, instrument, and account models alongside exchange integration boundaries. Develop automated testing strategies and perform evidence-based performance benchmarking and profiling. Collaborate directly with client teams, SREs, QA, and leadership to ensure exchange readiness and durable production fixes. Engage with client engineering and business stakeholders, communicating technical trade-offs clearly. Support the product in production across multiple client deployments. (And after six months) Independently own key technical workstreams from concept to production readiness. Deliver maintainable, observable, and well-tested systems aligned with core architecture. Establish trusted relationships with clients through clear communication and steady delivery. WHY US: To be immersed in high-standard engineering culture. Our fantastic team takes pride in crafting complex technical solutions but also loves sharing their knowledge and helping you grow professionally (we have extraordinary minds at Adaptive, you can learn from anyone here, which is the beauty of it). To take part in the growth and development of a great company. Our teams feel free to speak up, make suggestions and raise concerns. Collaborative team environment: we all work together, respect each other, and pitch in Great consideration for work/life balance (highly-flexible, hybrid working model, well-being benefits ). The balance between professional and personal life is massively important to us. We work hard to provide a positive, collaborative and inclusive culture and to positively impact our staff and local communities through different well-being, diversity and inclusion programmes. WHAT PEOPLE THINK OF US You can check our Glassdoor page BENEFITS (What we offer in return what you'll get ): For permanents: We create benefits with YOU in mind. We create benefits with YOU in mind: Flexible hybrid working model Medical from the 1st of the following month of your start date (i.e. if you join on the 24th of July, it starts on the 1st of August). We have 6 Aetna plans to choose from as provided by our PEO, Justworks. We make a flat monthly contribution to your healthcare costs Dental and vision from the 1st of the month following your start date - we have 3 dental and 2 vision plans to choose from. We make fixed contributions to each 23 days of vacation per calendar year plus 11 public holidays Group disability insurance: short-term and long-term (60% and taxable) 401K safe harbor plan where we match contributions up to 5% of base pay on a paycheck-to-paycheck basis (you can opt-in after 90 days of service) Gym subsidy of up to $50 per month (and we pay the taxes on that so it's a real $50) post probation Life insurance at 2 x salary Commuter benefits Health Savings Account and Flexible Spending Account Mental Health First Aiders THE PROCESS Long interview processes are stressful and boring and that is not us! We want to make sure that everything runs smoothly. So here you will have three-stage interviews: 1- A chat with one of our great recruiters. 2- A Zoom chat with one of our Java colleagues where they will ask you detailed questions about your experience. 3- A Face to Face interview (either in our office or via Zoom). During this interview, we will dig even deeper and you will have a pair programming task to do. But don't worry; everything will be explained to you step by step by your recruiter. A little tip for you during those stages: Collaboration is massively important to us, so don't hesitate to share your thoughts, ask questions, ask for help if needed, etc DIVERSITY & INCLUSION: Diversity and inclusion are key to a great workplace, and Adaptive is better when it's more representative of the world around us. We want everyone to feel comfortable bringing their whole selves to work without any fear of judgment or negativity. All we ask is that our colleagues are respectful, collaborative, passionate about what they do, and have the skills needed to be successful in their roles. Background check: the employment/engagement is subject to an acceptable background check that will be run by Adaptive. E-verify: Adaptive Financial Consulting Inc. makes use of E-Verify to validate someone's right to work in the US. We will provide the Social Security Administration, and, if necessary, the Department of Homeland Security, with information from each new employee's Form I-9 to confirm work authorization. Please note that we do not use this information to pre-screen job applicants. Base pay will be determined on an individualized basis and is only part of the total compensation package. Pay is based on candidate skills and experience.New York pay range$240,000-$260,000 USD
Job Description Job Description Hello, "Join GD Resources for dynamic opportunities in business management and IT, where innovation meets excellence." About the Company: GD Resources is a Veteran Women-Owned Business Management and Information Technology company committed to excellence. GD Resources provides dynamic opportunities for veterans and professionals alike to contribute to innovative projects and drive success in a collaborative and supportive environment. Join us to make a difference, advance your career, and grow with a company that values integrity, diversity, and continuous improvement. Experience8-12 YearsClientNew York City - DoITTDuration6 MonthsPrimary SkillsIOS, Android, JIRA, azure, Product Manager, Trello, DevOpLocation Brooklyn, NY, 11201 Job Start Date2026-05-04Remote JobNoRequired Hours/Week35Job TypeContract Public Job TitleMid Level - Mobile App Developer (iOS & Android)Public Job DescriptionNYC Office of Technology and Innovation Job Title: Mid Level - Mobile App Developer (iOS & Android) Duration: 6+ Months with possible extension Location: 15 Metrotech Center, Brooklyn, NY 11201 Position Type: Contract Interview Type: Webcam/In-person Note: Normal Business Hours, Monday through Friday (not including a mandatory unpaid meal break after 6 hours of work), 35 work hours per week. If the consultant works more than 35 hours per week, the consultant must request overtime in the Agency's timekeeping system, and the project manager must approve those hours worked above the weekly maximum. SCOPE OF SERVICES: The developer will be responsible for overseeing the end-to-end technical execution of the new features in the NYC Secure App on iOS and Android and development of other digital resources as needed. The developer will deliver a scalable, privacy-centric systems that integrates with existing NYC data services, workflows, and web platforms. Job Description: The NYC Office of Technology and Innovation has been tasked with re-designing the NYC Secure App and an associated campaign to provide New Yorkers with a comprehensive set of tools and resources to prevent scam phone calls and text messages, educate vulnerable New Yorkers on prevention, and support New Yorkers with the resources they need when they have been victimized. Each year New Yorkers lose an estimated $6.5B to online and phone based scams, yet the city provides no systematic approach to protecting residents - this project will develop the technology and strategy to address that gap across OTI's programs including Cybersecurity, 311, and Digital Equity. TASKS: Develop quality code that is well-documented, testable, and production-ready Be proactive and seek feedback to ensure best practice solutions that meet business needs Building web solutions that are scalable and secure and align with overall city digital architecture Write and conduct unit testing as agreed with the City Engineering leads. Communicate technical decisions, needs, and priorities to engineers, product managers, and designers as part of a user-centered agile product delivery team Design the core logic with the existing vendor for the mobile application on iOS and Android to provide scam and spam protection for calls and texts. Build a responsive, accessible frontends resource sites that ensures a consistent experience across all browser types and mobile devices and leverages the NYC Design System. Apply rigorous industry-standard privacy and security standards and protocols to ensure that all user data remains private and secure. Develop the technical bridges necessary to route digital reporting data into existing intake and reporting systems. If necessary, learn new programming languages or frameworks, with help from City Engineering leads, to complete software development and testing tasks. Attend, participate, and assist in architecture, approach, and technical strategies as appropriate and requested by City Engineering leads. Mandatory Skills: At least 4 years of experience as a software engineer or application developer Experience building responsive websites with full-stack expertise Experience collaborating with product designers on cross-functional teams to ensure the best user experience. Experience working with Git based workflows Experience working in story-based workflows (e.g., Azure DevOps, JIRA, Trello, or other story or kanban-style workflow) Experience leading technical design and writing implementation planning documents Strong verbal and written communication skills Regards, Srikanth (Sri) Senior Recruiter Phone: Email: Powered by JazzHR I8bEmzW0Mq
10/30/2026
Full time
Job Description Job Description Hello, "Join GD Resources for dynamic opportunities in business management and IT, where innovation meets excellence." About the Company: GD Resources is a Veteran Women-Owned Business Management and Information Technology company committed to excellence. GD Resources provides dynamic opportunities for veterans and professionals alike to contribute to innovative projects and drive success in a collaborative and supportive environment. Join us to make a difference, advance your career, and grow with a company that values integrity, diversity, and continuous improvement. Experience8-12 YearsClientNew York City - DoITTDuration6 MonthsPrimary SkillsIOS, Android, JIRA, azure, Product Manager, Trello, DevOpLocation Brooklyn, NY, 11201 Job Start Date2026-05-04Remote JobNoRequired Hours/Week35Job TypeContract Public Job TitleMid Level - Mobile App Developer (iOS & Android)Public Job DescriptionNYC Office of Technology and Innovation Job Title: Mid Level - Mobile App Developer (iOS & Android) Duration: 6+ Months with possible extension Location: 15 Metrotech Center, Brooklyn, NY 11201 Position Type: Contract Interview Type: Webcam/In-person Note: Normal Business Hours, Monday through Friday (not including a mandatory unpaid meal break after 6 hours of work), 35 work hours per week. If the consultant works more than 35 hours per week, the consultant must request overtime in the Agency's timekeeping system, and the project manager must approve those hours worked above the weekly maximum. SCOPE OF SERVICES: The developer will be responsible for overseeing the end-to-end technical execution of the new features in the NYC Secure App on iOS and Android and development of other digital resources as needed. The developer will deliver a scalable, privacy-centric systems that integrates with existing NYC data services, workflows, and web platforms. Job Description: The NYC Office of Technology and Innovation has been tasked with re-designing the NYC Secure App and an associated campaign to provide New Yorkers with a comprehensive set of tools and resources to prevent scam phone calls and text messages, educate vulnerable New Yorkers on prevention, and support New Yorkers with the resources they need when they have been victimized. Each year New Yorkers lose an estimated $6.5B to online and phone based scams, yet the city provides no systematic approach to protecting residents - this project will develop the technology and strategy to address that gap across OTI's programs including Cybersecurity, 311, and Digital Equity. TASKS: Develop quality code that is well-documented, testable, and production-ready Be proactive and seek feedback to ensure best practice solutions that meet business needs Building web solutions that are scalable and secure and align with overall city digital architecture Write and conduct unit testing as agreed with the City Engineering leads. Communicate technical decisions, needs, and priorities to engineers, product managers, and designers as part of a user-centered agile product delivery team Design the core logic with the existing vendor for the mobile application on iOS and Android to provide scam and spam protection for calls and texts. Build a responsive, accessible frontends resource sites that ensures a consistent experience across all browser types and mobile devices and leverages the NYC Design System. Apply rigorous industry-standard privacy and security standards and protocols to ensure that all user data remains private and secure. Develop the technical bridges necessary to route digital reporting data into existing intake and reporting systems. If necessary, learn new programming languages or frameworks, with help from City Engineering leads, to complete software development and testing tasks. Attend, participate, and assist in architecture, approach, and technical strategies as appropriate and requested by City Engineering leads. Mandatory Skills: At least 4 years of experience as a software engineer or application developer Experience building responsive websites with full-stack expertise Experience collaborating with product designers on cross-functional teams to ensure the best user experience. Experience working with Git based workflows Experience working in story-based workflows (e.g., Azure DevOps, JIRA, Trello, or other story or kanban-style workflow) Experience leading technical design and writing implementation planning documents Strong verbal and written communication skills Regards, Srikanth (Sri) Senior Recruiter Phone: Email: Powered by JazzHR I8bEmzW0Mq
Job Description Job Description Interested in building the next viral IOS app - even bigger than Duolingo? Imagine a world where studying feels like play-where SAT prep is as addictive as scrolling through TikTok or diving into a game of Geoguessr/Trivia Crack. That's exactly our mission - make learning FUN. And we're bringing it to life by building Duolingo for school. We call it Brainblast, and we need YOU to help us build it. We're turning studying into a game - a cracked out, viral iPhone game. To learn more about our vision & the app, visit About us: Brainblast is a new product by Smart Nonsense - a media company making learning fun with over 3 billion views generated worldwide. Requirements The Role: This is a fully remote position, open to candidates worldwide. As the sole engineer/dev, you'll need to take on full-stack responsibilities ensuring smooth front-end and back-end interactions. You will Take full ownership of developing, launching, and maintaining the iOS app Build rapid prototypes for internal testing 2-3x/week Develop an asynchronous game experience where users solve and send math problems to friends. Implement analytics to track student progress and help users identify weak areas for improvement. Take ownership of formatting and integrating question banks into the app. Build a seamless content delivery system for a TikTok-style mobile video course. Optimize the app for a highly engaging, fast, and smooth learning experience. Ensure the app is scalable, maintainable, and bug-free through rigorous testing and code reviews. Who you are: You're not just an executor-you're an innovator. You thrive on creativity, constantly pushing boundaries with crazy, forward-thinking ideas. You don't wait for direction-you help define what's next with a strong sense of urgency. Qualifications: 3+ years of professional software experience in iOS app development. Shipped at least one iOS app professionally Proficient with Swift, IOS frameworks (UIKit, CoreData, Core Animation, etc.) and IOS SDK performance tools. Experience with Experience with RESTful APIs & other API integrations Knowledge of video streaming and optimization Familiarity with Firebase or other backend solutions. Experience with integrating advanced analytics, animations, and gamified features. Benefits 1) Above-market pay 2) Work from home - No meetings, schedules, or ASAPs. Work whenever, wherever, and however you want. 3) Paid holiday & time off - The best need breaks. 4) Growth opportunities internally Our goal is to work together for decades, not months.
10/30/2026
Full time
Job Description Job Description Interested in building the next viral IOS app - even bigger than Duolingo? Imagine a world where studying feels like play-where SAT prep is as addictive as scrolling through TikTok or diving into a game of Geoguessr/Trivia Crack. That's exactly our mission - make learning FUN. And we're bringing it to life by building Duolingo for school. We call it Brainblast, and we need YOU to help us build it. We're turning studying into a game - a cracked out, viral iPhone game. To learn more about our vision & the app, visit About us: Brainblast is a new product by Smart Nonsense - a media company making learning fun with over 3 billion views generated worldwide. Requirements The Role: This is a fully remote position, open to candidates worldwide. As the sole engineer/dev, you'll need to take on full-stack responsibilities ensuring smooth front-end and back-end interactions. You will Take full ownership of developing, launching, and maintaining the iOS app Build rapid prototypes for internal testing 2-3x/week Develop an asynchronous game experience where users solve and send math problems to friends. Implement analytics to track student progress and help users identify weak areas for improvement. Take ownership of formatting and integrating question banks into the app. Build a seamless content delivery system for a TikTok-style mobile video course. Optimize the app for a highly engaging, fast, and smooth learning experience. Ensure the app is scalable, maintainable, and bug-free through rigorous testing and code reviews. Who you are: You're not just an executor-you're an innovator. You thrive on creativity, constantly pushing boundaries with crazy, forward-thinking ideas. You don't wait for direction-you help define what's next with a strong sense of urgency. Qualifications: 3+ years of professional software experience in iOS app development. Shipped at least one iOS app professionally Proficient with Swift, IOS frameworks (UIKit, CoreData, Core Animation, etc.) and IOS SDK performance tools. Experience with Experience with RESTful APIs & other API integrations Knowledge of video streaming and optimization Familiarity with Firebase or other backend solutions. Experience with integrating advanced analytics, animations, and gamified features. Benefits 1) Above-market pay 2) Work from home - No meetings, schedules, or ASAPs. Work whenever, wherever, and however you want. 3) Paid holiday & time off - The best need breaks. 4) Growth opportunities internally Our goal is to work together for decades, not months.
Job Description Job Description Primary Talent Partners has a new contract opening for a Software Engineer III with our large power and utilities client in Charlotte, NC. This is a 12-month contract with a potential for extension. Pay: $65.00 - $75.00/hr ; W2 contract, no PTO, no Benefits. ACA-compliant supplemental package available for enrollment. Candidates must be legally authorized to work in the United States and must be able to sit on Primary Talent Partners W2 without sponsorship. Description: Seeking an experienced engineer to provide application support, maintenance, enhancement, and operational oversight for a business-critical physical security and access management platform. This role requires a senior, hands-on resource who can take ownership of a complex AWS-hosted application and troubleshoot across front-end technologies, cloud services, databases, APIs, identity controls, and physical security integrations. This is not solely a front-end development role or an AWS infrastructure role. The ideal candidate will bring broad application support expertise, strong troubleshooting capabilities, and experience supporting cloud-native enterprise applications across infrastructure, integrations, security, and reporting domains. Core Responsibilities: Provide day-to-day production support for a cloud-based access management platform. Troubleshoot application, integration, and data issues across UI, APIs, messaging, and databases. Support AWS Lambda-based services and release/deployment workflows. Monitor application health, investigate incidents, and drive root cause analysis (RCA). Partner with business stakeholders, vendors, and internal platform/security teams. Maintain technical documentation, runbooks, and support procedures. Support audit/compliance needs and operational reporting. Required Skills (Must Have): Angular and TypeScript (production support and troubleshooting) AWS Lambda (Python and/or .NET) REST API and integration troubleshooting Kafka SQL Server (MSSQL) and PostgreSQL GitHub and GitHub Actions AWS AI/ML integrations (Bedrock, Textract, Rekognition) Monitoring and incident response (CloudWatch, Dynatrace, Splunk, or equivalent) Reporting experience (Power BI, SSRS, or equivalent), including audit and operational reporting Nice-to-Have Skills: AWS services: Connect, Lex, Aurora, RDS, S3, CloudFront AWS security services: IAM, KMS, Secrets Manager Identity and access technologies: Active Directory, Entra ID, RBAC, CyberArk Akamai Terraform or CloudFormation Automated testing tools (Tricentis preferred) Industry/Domain Experience (Preferred) Physical security and access-control platform support Integrations with systems such as Avigilon, Symmetry, gate controllers, and intercom/callbox solutions Experience in regulated/compliance -driven environments Soft Skills: Strong analytical thinking and advanced troubleshooting/problem -solving ability Ability to manage multiple priorities in a fast-paced production support environment Clear written and verbal communication with technical and non-technical stakeholders Proven collaboration with vendors, business partners, infrastructure teams, and security teams Self-motivated, accountable, and able to work independently with minimal oversight Strong documentation discipline (runbooks, incident notes, RCA, and operational procedures) 24x7 production support and on-call participation Desired Candidate Profile: 5+ years supporting enterprise applications in production 3+ years supporting AWS cloud-native/serverless solutions Strong analytical troubleshooting and communication skills Ability to manage multiple priorities and work independently Primary Talent Partners is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws. If you are a person with a disability needing assistance with the application or at any point in the hiring process, please contact us at
10/30/2026
Full time
Job Description Job Description Primary Talent Partners has a new contract opening for a Software Engineer III with our large power and utilities client in Charlotte, NC. This is a 12-month contract with a potential for extension. Pay: $65.00 - $75.00/hr ; W2 contract, no PTO, no Benefits. ACA-compliant supplemental package available for enrollment. Candidates must be legally authorized to work in the United States and must be able to sit on Primary Talent Partners W2 without sponsorship. Description: Seeking an experienced engineer to provide application support, maintenance, enhancement, and operational oversight for a business-critical physical security and access management platform. This role requires a senior, hands-on resource who can take ownership of a complex AWS-hosted application and troubleshoot across front-end technologies, cloud services, databases, APIs, identity controls, and physical security integrations. This is not solely a front-end development role or an AWS infrastructure role. The ideal candidate will bring broad application support expertise, strong troubleshooting capabilities, and experience supporting cloud-native enterprise applications across infrastructure, integrations, security, and reporting domains. Core Responsibilities: Provide day-to-day production support for a cloud-based access management platform. Troubleshoot application, integration, and data issues across UI, APIs, messaging, and databases. Support AWS Lambda-based services and release/deployment workflows. Monitor application health, investigate incidents, and drive root cause analysis (RCA). Partner with business stakeholders, vendors, and internal platform/security teams. Maintain technical documentation, runbooks, and support procedures. Support audit/compliance needs and operational reporting. Required Skills (Must Have): Angular and TypeScript (production support and troubleshooting) AWS Lambda (Python and/or .NET) REST API and integration troubleshooting Kafka SQL Server (MSSQL) and PostgreSQL GitHub and GitHub Actions AWS AI/ML integrations (Bedrock, Textract, Rekognition) Monitoring and incident response (CloudWatch, Dynatrace, Splunk, or equivalent) Reporting experience (Power BI, SSRS, or equivalent), including audit and operational reporting Nice-to-Have Skills: AWS services: Connect, Lex, Aurora, RDS, S3, CloudFront AWS security services: IAM, KMS, Secrets Manager Identity and access technologies: Active Directory, Entra ID, RBAC, CyberArk Akamai Terraform or CloudFormation Automated testing tools (Tricentis preferred) Industry/Domain Experience (Preferred) Physical security and access-control platform support Integrations with systems such as Avigilon, Symmetry, gate controllers, and intercom/callbox solutions Experience in regulated/compliance -driven environments Soft Skills: Strong analytical thinking and advanced troubleshooting/problem -solving ability Ability to manage multiple priorities in a fast-paced production support environment Clear written and verbal communication with technical and non-technical stakeholders Proven collaboration with vendors, business partners, infrastructure teams, and security teams Self-motivated, accountable, and able to work independently with minimal oversight Strong documentation discipline (runbooks, incident notes, RCA, and operational procedures) 24x7 production support and on-call participation Desired Candidate Profile: 5+ years supporting enterprise applications in production 3+ years supporting AWS cloud-native/serverless solutions Strong analytical troubleshooting and communication skills Ability to manage multiple priorities and work independently Primary Talent Partners is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws. If you are a person with a disability needing assistance with the application or at any point in the hiring process, please contact us at
Salesforce Architect/Sr. Administrator Why You'll Love Working Here: Comprehensive Benefits: Medical, Dental, and Vision Insurance. Secure Your Future: 401K with a generous company match. Time to Recharge: Generous PTO - start accruing from day one! Balanced Schedule: Enjoy great work-life harmony with a friendly Monday-Friday schedule. Celebrate & Connect: Participate in engaging company-wide events, team-building activities, and employee recognition programs. Onsite Perks: Access our fitness center, relax in team lounge areas, or enjoy food trucks and courtyard spaces. Growth & Coaching: Learn from industry professionals committed to your success. Diverse & Inclusive: We embrace what makes each team member unique! About the Role As a full-time Salesforce Architect/Sr. Administrator, you'll direct Wesley's 350-user Salesforce org, our system of record for sales and client resolution, reporting to the Director of Development. He ran this org for eight years before moving into that role, so you'll get a real handoff from someone who helped build it. Our platform engineering team is building products alongside Salesforce, starting with the Wesley Client Portal, and we're open to evaluating our long-term platform options as the technology changes. We build with Claude Code every day, and we need someone with the depth to catch what AI gets wrong before it reaches production. What You'll Do Architecture and security Set the target-state design, data model, and roadmap Act as design authority for every change, and push back on solutions that create future debt Maintain the security and sharing model, SSO, and least-privilege access for sensitive client data Build and maintain Build Flows and Apex, hands-on and with frontier AI tools like Claude Code Set the review standards, test coverage, and Copado deployment controls others build within Find and clean up technical debt: overlapping automation, aging Apex, and unused fields Keep our AppExchange apps healthy, including DocuSign, Omnito, Goat Email, and Distribution Engine Manage OwnBackup for backup, archiving, sandbox seeding, and recovery Advise on which AppExchange apps earn their cost and which could be rebuilt in-house Integrations Build and own integrations between Salesforce and external systems, including NetSuite, Five9, and the Wesley Client Portal Serve as the Salesforce authority for the platform engineering team What You Need Titles don't matter. Admins who taught themselves Apex are welcome. 6+ years hands-on Salesforce, most of it owning a production org Real depth in Flow, Apex, and SOQL, and judgment about when declarative beats code A habit of using AI tools to speed up solution design, automate repetitive admin work, and ship faster Experience paying down technical debt without disrupting production Experience integrating Salesforce with external platforms through REST and Bulk APIs, middleware such as n8n, Zapier, or Workato, or direct callouts Experience designing and maintaining security and data access controls Experience gathering requirements from business stakeholders and turning them into working solutions DevOps experience with Copado or similar Good instincts about sensitive client data in AI workflows Salesforce Certified Administrator U.S.-based; we can't sponsor visas Nice to Haves Advanced Administrator, Platform App Builder, or Application/System Architect certification Experience with Five9 or another major telephony platform Experience replacing an AppExchange package with a custom build Based near Nashville Ready to Make a Difference? This is more than just a job - it's your chance to be part of something meaningful, in a workplace that values your unique talents and fosters your professional growth. Apply now and discover what makes Wesley Financial Group truly stand out. We can't wait to welcome you to the team! Please remember to check both your inbox and spam folders for all application and interview-related communications after you apply. PIfcc6b90db6-
10/30/2026
Full time
Salesforce Architect/Sr. Administrator Why You'll Love Working Here: Comprehensive Benefits: Medical, Dental, and Vision Insurance. Secure Your Future: 401K with a generous company match. Time to Recharge: Generous PTO - start accruing from day one! Balanced Schedule: Enjoy great work-life harmony with a friendly Monday-Friday schedule. Celebrate & Connect: Participate in engaging company-wide events, team-building activities, and employee recognition programs. Onsite Perks: Access our fitness center, relax in team lounge areas, or enjoy food trucks and courtyard spaces. Growth & Coaching: Learn from industry professionals committed to your success. Diverse & Inclusive: We embrace what makes each team member unique! About the Role As a full-time Salesforce Architect/Sr. Administrator, you'll direct Wesley's 350-user Salesforce org, our system of record for sales and client resolution, reporting to the Director of Development. He ran this org for eight years before moving into that role, so you'll get a real handoff from someone who helped build it. Our platform engineering team is building products alongside Salesforce, starting with the Wesley Client Portal, and we're open to evaluating our long-term platform options as the technology changes. We build with Claude Code every day, and we need someone with the depth to catch what AI gets wrong before it reaches production. What You'll Do Architecture and security Set the target-state design, data model, and roadmap Act as design authority for every change, and push back on solutions that create future debt Maintain the security and sharing model, SSO, and least-privilege access for sensitive client data Build and maintain Build Flows and Apex, hands-on and with frontier AI tools like Claude Code Set the review standards, test coverage, and Copado deployment controls others build within Find and clean up technical debt: overlapping automation, aging Apex, and unused fields Keep our AppExchange apps healthy, including DocuSign, Omnito, Goat Email, and Distribution Engine Manage OwnBackup for backup, archiving, sandbox seeding, and recovery Advise on which AppExchange apps earn their cost and which could be rebuilt in-house Integrations Build and own integrations between Salesforce and external systems, including NetSuite, Five9, and the Wesley Client Portal Serve as the Salesforce authority for the platform engineering team What You Need Titles don't matter. Admins who taught themselves Apex are welcome. 6+ years hands-on Salesforce, most of it owning a production org Real depth in Flow, Apex, and SOQL, and judgment about when declarative beats code A habit of using AI tools to speed up solution design, automate repetitive admin work, and ship faster Experience paying down technical debt without disrupting production Experience integrating Salesforce with external platforms through REST and Bulk APIs, middleware such as n8n, Zapier, or Workato, or direct callouts Experience designing and maintaining security and data access controls Experience gathering requirements from business stakeholders and turning them into working solutions DevOps experience with Copado or similar Good instincts about sensitive client data in AI workflows Salesforce Certified Administrator U.S.-based; we can't sponsor visas Nice to Haves Advanced Administrator, Platform App Builder, or Application/System Architect certification Experience with Five9 or another major telephony platform Experience replacing an AppExchange package with a custom build Based near Nashville Ready to Make a Difference? This is more than just a job - it's your chance to be part of something meaningful, in a workplace that values your unique talents and fosters your professional growth. Apply now and discover what makes Wesley Financial Group truly stand out. We can't wait to welcome you to the team! Please remember to check both your inbox and spam folders for all application and interview-related communications after you apply. PIfcc6b90db6-
Salesforce Architect/Sr. Administrator Why You'll Love Working Here: Comprehensive Benefits: Medical, Dental, and Vision Insurance. Secure Your Future: 401K with a generous company match. Time to Recharge: Generous PTO - start accruing from day one! Balanced Schedule: Enjoy great work-life harmony with a friendly Monday-Friday schedule. Celebrate & Connect: Participate in engaging company-wide events, team-building activities, and employee recognition programs. Onsite Perks: Access our fitness center, relax in team lounge areas, or enjoy food trucks and courtyard spaces. Growth & Coaching: Learn from industry professionals committed to your success. Diverse & Inclusive: We embrace what makes each team member unique! About the Role As a full-time Salesforce Architect/Sr. Administrator, you'll direct Wesley's 350-user Salesforce org, our system of record for sales and client resolution, reporting to the Director of Development. He ran this org for eight years before moving into that role, so you'll get a real handoff from someone who helped build it. Our platform engineering team is building products alongside Salesforce, starting with the Wesley Client Portal, and we're open to evaluating our long-term platform options as the technology changes. We build with Claude Code every day, and we need someone with the depth to catch what AI gets wrong before it reaches production. What You'll Do Architecture and security Set the target-state design, data model, and roadmap Act as design authority for every change, and push back on solutions that create future debt Maintain the security and sharing model, SSO, and least-privilege access for sensitive client data Build and maintain Build Flows and Apex, hands-on and with frontier AI tools like Claude Code Set the review standards, test coverage, and Copado deployment controls others build within Find and clean up technical debt: overlapping automation, aging Apex, and unused fields Keep our AppExchange apps healthy, including DocuSign, Omnito, Goat Email, and Distribution Engine Manage OwnBackup for backup, archiving, sandbox seeding, and recovery Advise on which AppExchange apps earn their cost and which could be rebuilt in-house Integrations Build and own integrations between Salesforce and external systems, including NetSuite, Five9, and the Wesley Client Portal Serve as the Salesforce authority for the platform engineering team What You Need Titles don't matter. Admins who taught themselves Apex are welcome. 6+ years hands-on Salesforce, most of it owning a production org Real depth in Flow, Apex, and SOQL, and judgment about when declarative beats code A habit of using AI tools to speed up solution design, automate repetitive admin work, and ship faster Experience paying down technical debt without disrupting production Experience integrating Salesforce with external platforms through REST and Bulk APIs, middleware such as n8n, Zapier, or Workato, or direct callouts Experience designing and maintaining security and data access controls Experience gathering requirements from business stakeholders and turning them into working solutions DevOps experience with Copado or similar Good instincts about sensitive client data in AI workflows Salesforce Certified Administrator U.S.-based; we can't sponsor visas Nice to Haves Advanced Administrator, Platform App Builder, or Application/System Architect certification Experience with Five9 or another major telephony platform Experience replacing an AppExchange package with a custom build Based near Nashville Ready to Make a Difference? This is more than just a job - it's your chance to be part of something meaningful, in a workplace that values your unique talents and fosters your professional growth. Apply now and discover what makes Wesley Financial Group truly stand out. We can't wait to welcome you to the team! Please remember to check both your inbox and spam folders for all application and interview-related communications after you apply. PIfcc6b90db6-
10/30/2026
Full time
Salesforce Architect/Sr. Administrator Why You'll Love Working Here: Comprehensive Benefits: Medical, Dental, and Vision Insurance. Secure Your Future: 401K with a generous company match. Time to Recharge: Generous PTO - start accruing from day one! Balanced Schedule: Enjoy great work-life harmony with a friendly Monday-Friday schedule. Celebrate & Connect: Participate in engaging company-wide events, team-building activities, and employee recognition programs. Onsite Perks: Access our fitness center, relax in team lounge areas, or enjoy food trucks and courtyard spaces. Growth & Coaching: Learn from industry professionals committed to your success. Diverse & Inclusive: We embrace what makes each team member unique! About the Role As a full-time Salesforce Architect/Sr. Administrator, you'll direct Wesley's 350-user Salesforce org, our system of record for sales and client resolution, reporting to the Director of Development. He ran this org for eight years before moving into that role, so you'll get a real handoff from someone who helped build it. Our platform engineering team is building products alongside Salesforce, starting with the Wesley Client Portal, and we're open to evaluating our long-term platform options as the technology changes. We build with Claude Code every day, and we need someone with the depth to catch what AI gets wrong before it reaches production. What You'll Do Architecture and security Set the target-state design, data model, and roadmap Act as design authority for every change, and push back on solutions that create future debt Maintain the security and sharing model, SSO, and least-privilege access for sensitive client data Build and maintain Build Flows and Apex, hands-on and with frontier AI tools like Claude Code Set the review standards, test coverage, and Copado deployment controls others build within Find and clean up technical debt: overlapping automation, aging Apex, and unused fields Keep our AppExchange apps healthy, including DocuSign, Omnito, Goat Email, and Distribution Engine Manage OwnBackup for backup, archiving, sandbox seeding, and recovery Advise on which AppExchange apps earn their cost and which could be rebuilt in-house Integrations Build and own integrations between Salesforce and external systems, including NetSuite, Five9, and the Wesley Client Portal Serve as the Salesforce authority for the platform engineering team What You Need Titles don't matter. Admins who taught themselves Apex are welcome. 6+ years hands-on Salesforce, most of it owning a production org Real depth in Flow, Apex, and SOQL, and judgment about when declarative beats code A habit of using AI tools to speed up solution design, automate repetitive admin work, and ship faster Experience paying down technical debt without disrupting production Experience integrating Salesforce with external platforms through REST and Bulk APIs, middleware such as n8n, Zapier, or Workato, or direct callouts Experience designing and maintaining security and data access controls Experience gathering requirements from business stakeholders and turning them into working solutions DevOps experience with Copado or similar Good instincts about sensitive client data in AI workflows Salesforce Certified Administrator U.S.-based; we can't sponsor visas Nice to Haves Advanced Administrator, Platform App Builder, or Application/System Architect certification Experience with Five9 or another major telephony platform Experience replacing an AppExchange package with a custom build Based near Nashville Ready to Make a Difference? This is more than just a job - it's your chance to be part of something meaningful, in a workplace that values your unique talents and fosters your professional growth. Apply now and discover what makes Wesley Financial Group truly stand out. We can't wait to welcome you to the team! Please remember to check both your inbox and spam folders for all application and interview-related communications after you apply. PIfcc6b90db6-
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work - and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. The Engineering and Sciences organization (E&S) pushes the boundaries of innovation, redefines engineering capabilities, and drives advances in various sciences. Our team is chartered with providing the skills, innovative technologies to develop, design, produce and sustain optimized product lines across the sector while providing a decisive advantage to the warfighter. Come be a part of our mission! Northrop Grumman Mission Systems' Baltimore and Partnered Sites (BaPs) division is seeking a Systems Integration & Test (SI&T) Engineers (Level 2 or Level 3) in Baltimore, MD to support test and verification activities of RF sensor systems. What you'll get to do: As the lead developer of radars, COMMS, and SIGINT for some of the most advanced systems in the U.S. arsenal, Northrop Grumman Mission Systems is a world leader in advanced sensor systems and design. These include airborne RADARs for fighter jets & UAVs including F-22, F-35, F-16, Global Hawk (Triton), and Gray Eagle (STARLite), airborne surveillance RADARs for AWACS and E-7 (MESA), and ground and maritime RADARs including G/ATOR and SEWIP. Qualified Systems Integration, Test & Evaluation (SITE) engineers will perform hands-on integration and testing of sophisticated RF sensor systems, including both hardware and software components in development and production environments; Synthesize internal and external customer needs and requirements into system tests that acknowledge technical and schedule constraints; Participate in the development and execution of comprehensive test plans, procedures, and schedules for verifying system requirements; participate in I&T readiness reviews, design reviews and conducts audits of I&T program facilities; Coordinate integrated testing activities that may include environmental, reliability and the occasional flight test; Review and evaluate test requirements to ensure completeness of test program; Perform analysis of test results and prepares comprehensive reports; Use modeling and simulation tools to expedite testing of individual units before all system components are available and for troubleshooting and repair of failed units. What You'll Get to Do: Experienced systems engineer providing technical leadership for ATP, Development I&T, and Capabilities I&T activities. This role leads test planning and execution, lab configuration management, and requirements verification across multiple SILs and benches, while mentoring early career engineers. Key responsibilities Lead lab and bench ownership Serve as lead maintainer for one or more integration labs/benches (e.g., SILs, Mode benches, MATE bays). Own bench design changes, maintenance planning, and configuration management of HW/SW, processors, and test equipment. Own test planning and execution Develop and lead LRIP ATP, HW DVT, and SSQT test plans, procedures, and success criteria. Define and manage regression test campaigns for system SW OFP, FW, FESW, BSCT and related components. Coordinate Mode SIL bench operations and flight test preparation and support, including objectives and No/Go criteria. Drive system integration of new capabilities Lead MATE and system integration of new advanced capabilities into SILs and lab environments. Ensure integration plans and test strategies support accelerated development and delivery schedules. Manage configuration and verification artifacts Own configuration management processes for MATE and system test environments, ensuring traceability and controlled changes. Lead PBS SE requirements verification, including VCRM content, verification documentation, and closure of requirements. Troubleshooting, coordination, and mentoring Lead HW/SW troubleshooting across multiple SILs and benches. Coordinate with SIT, TDE, FW, FESW, subsystem I&T, SEC, Mode, and other stakeholders as primary technical contact for integration and test issues. Mentor T02 engineers (Req A hires) in test design, execution, and verification practices. This is a 2nd shift position This requisition may be filled at a higher grade based on qualifications listed below This requisition may be filled at either a Principal Level or a Sr. Principal Level. Basic Qualifications for a Principal Systems Engineer - Integration & Test Bachelor's degree in a STEM discipline or related field with 5+ years of relevant experience with; 3+ years with a Master's; 1+ year with a PhD. Demonstrated experience in system integration and test on complex HW/SW systems, preferably in defense or aerospace. Experience leading lab/bench ownership, test campaigns, or requirements verification activities. Strong communication and leadership skills; ability to coordinate across multiple teams and present technical status to management and customers. Active DoD Secret clearance and the ability to obtain/maintain Special Program Access (SAP) prior to start is required. Candidate must be a US citizen Ability to work onsite in Baltimore, MD. Willingness to work 2nd shift Basic Qualifications for a Principal Systems Engineer - Integration & Test Bachelor's degree in a STEM discipline or related field with 8+ years of relevant experience with; 6+ years with a Master's; 4+ year with a PhD. Demonstrated experience in system integration and test on complex HW/SW systems, preferably in defense or aerospace. Experience leading lab/bench ownership, test campaigns, or requirements verification activities. Strong communication and leadership skills; ability to coordinate across multiple teams and present technical status to management and customers. Active DoD Secret clearance and the ability to obtain/maintain Special Program Access (SAP) prior to start is required. Candidate must be a US citizen Ability to work onsite in Baltimore, MD. Willingness to work 2nd shift Preferred qualifications Prior experience on Tactical Radar Programs or similar mission systems. Familiarity with configuration management tools and disciplined processes for complex test environments. Experience directing flight test objectives, No/Go criteria, and test configuration. This position is contingent upon transfer of active DoD Secret Clearance and approved special program access. Primary Level Salary Range: $108,800.00 - $163,200.00 Secondary Level Salary Range: $135,800.00 - $203,600.00 The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business. The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
10/30/2026
Full time
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work - and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. The Engineering and Sciences organization (E&S) pushes the boundaries of innovation, redefines engineering capabilities, and drives advances in various sciences. Our team is chartered with providing the skills, innovative technologies to develop, design, produce and sustain optimized product lines across the sector while providing a decisive advantage to the warfighter. Come be a part of our mission! Northrop Grumman Mission Systems' Baltimore and Partnered Sites (BaPs) division is seeking a Systems Integration & Test (SI&T) Engineers (Level 2 or Level 3) in Baltimore, MD to support test and verification activities of RF sensor systems. What you'll get to do: As the lead developer of radars, COMMS, and SIGINT for some of the most advanced systems in the U.S. arsenal, Northrop Grumman Mission Systems is a world leader in advanced sensor systems and design. These include airborne RADARs for fighter jets & UAVs including F-22, F-35, F-16, Global Hawk (Triton), and Gray Eagle (STARLite), airborne surveillance RADARs for AWACS and E-7 (MESA), and ground and maritime RADARs including G/ATOR and SEWIP. Qualified Systems Integration, Test & Evaluation (SITE) engineers will perform hands-on integration and testing of sophisticated RF sensor systems, including both hardware and software components in development and production environments; Synthesize internal and external customer needs and requirements into system tests that acknowledge technical and schedule constraints; Participate in the development and execution of comprehensive test plans, procedures, and schedules for verifying system requirements; participate in I&T readiness reviews, design reviews and conducts audits of I&T program facilities; Coordinate integrated testing activities that may include environmental, reliability and the occasional flight test; Review and evaluate test requirements to ensure completeness of test program; Perform analysis of test results and prepares comprehensive reports; Use modeling and simulation tools to expedite testing of individual units before all system components are available and for troubleshooting and repair of failed units. What You'll Get to Do: Experienced systems engineer providing technical leadership for ATP, Development I&T, and Capabilities I&T activities. This role leads test planning and execution, lab configuration management, and requirements verification across multiple SILs and benches, while mentoring early career engineers. Key responsibilities Lead lab and bench ownership Serve as lead maintainer for one or more integration labs/benches (e.g., SILs, Mode benches, MATE bays). Own bench design changes, maintenance planning, and configuration management of HW/SW, processors, and test equipment. Own test planning and execution Develop and lead LRIP ATP, HW DVT, and SSQT test plans, procedures, and success criteria. Define and manage regression test campaigns for system SW OFP, FW, FESW, BSCT and related components. Coordinate Mode SIL bench operations and flight test preparation and support, including objectives and No/Go criteria. Drive system integration of new capabilities Lead MATE and system integration of new advanced capabilities into SILs and lab environments. Ensure integration plans and test strategies support accelerated development and delivery schedules. Manage configuration and verification artifacts Own configuration management processes for MATE and system test environments, ensuring traceability and controlled changes. Lead PBS SE requirements verification, including VCRM content, verification documentation, and closure of requirements. Troubleshooting, coordination, and mentoring Lead HW/SW troubleshooting across multiple SILs and benches. Coordinate with SIT, TDE, FW, FESW, subsystem I&T, SEC, Mode, and other stakeholders as primary technical contact for integration and test issues. Mentor T02 engineers (Req A hires) in test design, execution, and verification practices. This is a 2nd shift position This requisition may be filled at a higher grade based on qualifications listed below This requisition may be filled at either a Principal Level or a Sr. Principal Level. Basic Qualifications for a Principal Systems Engineer - Integration & Test Bachelor's degree in a STEM discipline or related field with 5+ years of relevant experience with; 3+ years with a Master's; 1+ year with a PhD. Demonstrated experience in system integration and test on complex HW/SW systems, preferably in defense or aerospace. Experience leading lab/bench ownership, test campaigns, or requirements verification activities. Strong communication and leadership skills; ability to coordinate across multiple teams and present technical status to management and customers. Active DoD Secret clearance and the ability to obtain/maintain Special Program Access (SAP) prior to start is required. Candidate must be a US citizen Ability to work onsite in Baltimore, MD. Willingness to work 2nd shift Basic Qualifications for a Principal Systems Engineer - Integration & Test Bachelor's degree in a STEM discipline or related field with 8+ years of relevant experience with; 6+ years with a Master's; 4+ year with a PhD. Demonstrated experience in system integration and test on complex HW/SW systems, preferably in defense or aerospace. Experience leading lab/bench ownership, test campaigns, or requirements verification activities. Strong communication and leadership skills; ability to coordinate across multiple teams and present technical status to management and customers. Active DoD Secret clearance and the ability to obtain/maintain Special Program Access (SAP) prior to start is required. Candidate must be a US citizen Ability to work onsite in Baltimore, MD. Willingness to work 2nd shift Preferred qualifications Prior experience on Tactical Radar Programs or similar mission systems. Familiarity with configuration management tools and disciplined processes for complex test environments. Experience directing flight test objectives, No/Go criteria, and test configuration. This position is contingent upon transfer of active DoD Secret Clearance and approved special program access. Primary Level Salary Range: $108,800.00 - $163,200.00 Secondary Level Salary Range: $135,800.00 - $203,600.00 The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business. The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
Job Description Job Description The Performance & Insights Engineer sits within SM Energy's Enterprise Performance & Insights team, reporting into the Chief Operating Officer organization, and works at the intersection of petroleum engineering, data engineering, and executive decision support. This role translates complex subsurface, operational, and financial data into high-impact analyses, models, and executive-ready deliverables that inform Investor Relations (IR) and Board of Directors (BOD) communications and advance critical strategic initiatives. Combining a working command of operational and asset engineering fundamentals with full-stack data wrangling and coding capability and modern AI-assisted workflows, the engineer independently frames ambiguous business problems, builds scalable end-to-end analytical solutions, and communicates insights persuasively to senior leadership. Operates under limited review while handling assignments of broad scope and complex difficulty; may mentor less experienced analysts and engineers and supervise their technical work. Essential Roles and Responsibilities Translate complex operational, development, and financial business problems into end-to-end analytical solutions - from data acquisition and pipeline through model, visualization, and executive-ready deliverable. Build, maintain, and optimize data pipelines, queries, and analytics data views across production, reservoir, financial, and capital-planning domains using SQL and Python; design and test scripts, stored procedures, functions, and views. Deliver executive and Board-ready artifacts through an agentic, AI-assisted workflow - directing tools such as Claude to build self-contained HTML dashboards, branded decks, and models from a spec, then refining them while retaining judgment over accuracy and design. Understanding of production and reservoir engineering fundamentals - decline curve analysis (DCA), rate/pressure transient analysis (RTA/PTA), volumetrics, EURs, artificial lift, and production optimization - to QA/QC data and pressure-test analytical results for physical reasonableness. Develop capital-efficiency, production-performance, operational KPIs, and economic metrics and models that support budgeting, forecasting, and strategic decision-making across operating regions. Design and produce executive-facing reporting - BOD slides, IR materials, and interactive dashboards - built to SM Energy brand standards. Leverage AI tools (e.g., large language model assistants such as Claude) to accelerate code development, data QA/QC, documentation, and analysis, applying sound engineering judgment to validate and stress-test AI-assisted output. Develop correlations between geological, completion, operational, and financial variables and well- and asset-level performance. Perform ad-hoc analyses; troubleshoot data-quality issues across the business; proactively identify potential issues and recommend solutions. Serve as a liaison across Operations, Finance, IR, Reservoir/Asset teams, and IT/Data - bridging deeply technical work and business audiences. Monitor production, capital, and financial data for discrepancies and opportunities; recommend operational and process improvements. Contribute to data governance, code documentation, change-release process, and best practices; educate others in support of a data- and AI-first culture. Manage and engage in multiple initiatives simultaneously; independently prioritize tasks and eliminate roadblocks to meet target deadlines. Conduct business with the highest ethical standards; demonstrate decision-making that ensures the safety of all people associated with SM facilities. Other duties as assigned. Role-Specific Technical Knowledge & Skills Petroleum Engineering. Working command of production operations, artificial-lift applications, and fundamental reservoir engineering disciplines - decline curve analysis, rate/pressure transient analysis, volumetrics, recoveries, EURs, and recovery factors. Understanding of unconventional resource plays across multiple basins/operating regions and familiarity with reserves, economics, AFE, and capital-planning workflows. Ability to identify limitations and ranges of certainty in a data set and to relate reservoir, completion, and operational characteristics to well performance. Data Engineering & Analytics. Advanced ability to wrangle, pre-process, and feature-engineer data and to connect data from disparate sources to surface insights, data-quality issues, and variable correlations. Sound applied-statistics foundation; competence with machine-learning concepts and frameworks a plus. End-to-end pipeline design that is cost-effective and scalable; strong code documentation and change-management discipline. AI-Augmented Delivery. Ability to integrate AI tools into daily delivery to compress cycle time while retaining engineering ownership of correctness - treating AI output as a draft to be verified, not a final answer. Understands data-security and data-privacy implications of AI-assisted and cloud-based workflows and accounts for them appropriately. Computer/Software Applications Programming & Analytics: Advanced SQL and Python (pandas, numpy, and related data ecosystem); R or comparable a plus. Data Platforms & Architecture: Data virtualization via Denodo; Snowflake and/or Databricks; Palantir Foundry; relational database design; ETL/ELT (dbt, SSIS); cloud environments (Azure, AWS). Visualization & Reporting: Governed enterprise BI (Power BI, Spotfire, or Tableau) for refreshing dashboards, plus bespoke interactive tools built as self-contained HTML dashboards (D3, Plotly, Recharts) that run anywhere without a license or server. Advanced PowerPoint and Excel for executive and Board deliverables, produced to SM Energy brand standards. Development Tools: Git/GitHub, modern IDEs (VS Code, PyCharm), notebooks (Jupyter), and fast dependency/environment management (uv, Poetry, conda). Comfortable in the agentic developer loop - coding assistants such as Claude Code, Cursor, or GitHub Copilot working inside the IDE/terminal, not used only as a side chat. Agentic Delivery: Fluent in AI-assisted artifact creation - directing agentic tools (e.g., Claude) to build branded HTML dashboards, PowerPoint decks, and Excel models end to end from a specification, then refining them iteratively. Applies SM's visual standards programmatically ("brand-as-code") so output is board-ready by default, and exercises judgment over layout, data integrity, and narrative clarity rather than accepting first-pass output. AI-Augmented Development: Fluent in an AI-native analytics workflow - uses LLM assistants (e.g., Claude) and agentic tools to accelerate development, QA/QC, refactoring, and documentation, always validating output against engineering judgment. Can leverage the Model Context Protocol (MCP) to connect AI agents securely to enterprise data and tools (e.g., querying Denodo or Snowflake, drafting Office deliverables) and platform-native AI such as Snowflake Cortex and Power BI Copilot, keeping data security and governance front of mind. Petroleum Engineering Software: Aries, Wellview, and Spotfire; exposure to RTA/PTA and production-analysis tools; reservoir simulation and frac models a plus. Education Bachelor's degree required in Petroleum, Chemical, or Mechanical Engineering; Data Science; Computer Science; Statistics; or a related quantitative field. A dual foundation in engineering and computing/data is strongly preferred. Advanced degree a plus. Typical Experience Minimum of 6 years of relevant experience. Experience should span both petroleum engineering (production/operations, and/or reservoir) and hands-on data/analytics development. Demonstrated delivery of executive- or Board-facing analytical work is strongly preferred. SM Energy offers competitive compensation and benefits programs which include, but are not limited to, variable pay, health care coverage, retirement plan, protection coverage, time off and leave programs, training and development opportunities and a range of allowances connected to specific work situations. Details are available at Careers SM Energy Company (SM) (). Applications will be accepted on an ongoing basis until the position is filled.
10/28/2026
Full time
Job Description Job Description The Performance & Insights Engineer sits within SM Energy's Enterprise Performance & Insights team, reporting into the Chief Operating Officer organization, and works at the intersection of petroleum engineering, data engineering, and executive decision support. This role translates complex subsurface, operational, and financial data into high-impact analyses, models, and executive-ready deliverables that inform Investor Relations (IR) and Board of Directors (BOD) communications and advance critical strategic initiatives. Combining a working command of operational and asset engineering fundamentals with full-stack data wrangling and coding capability and modern AI-assisted workflows, the engineer independently frames ambiguous business problems, builds scalable end-to-end analytical solutions, and communicates insights persuasively to senior leadership. Operates under limited review while handling assignments of broad scope and complex difficulty; may mentor less experienced analysts and engineers and supervise their technical work. Essential Roles and Responsibilities Translate complex operational, development, and financial business problems into end-to-end analytical solutions - from data acquisition and pipeline through model, visualization, and executive-ready deliverable. Build, maintain, and optimize data pipelines, queries, and analytics data views across production, reservoir, financial, and capital-planning domains using SQL and Python; design and test scripts, stored procedures, functions, and views. Deliver executive and Board-ready artifacts through an agentic, AI-assisted workflow - directing tools such as Claude to build self-contained HTML dashboards, branded decks, and models from a spec, then refining them while retaining judgment over accuracy and design. Understanding of production and reservoir engineering fundamentals - decline curve analysis (DCA), rate/pressure transient analysis (RTA/PTA), volumetrics, EURs, artificial lift, and production optimization - to QA/QC data and pressure-test analytical results for physical reasonableness. Develop capital-efficiency, production-performance, operational KPIs, and economic metrics and models that support budgeting, forecasting, and strategic decision-making across operating regions. Design and produce executive-facing reporting - BOD slides, IR materials, and interactive dashboards - built to SM Energy brand standards. Leverage AI tools (e.g., large language model assistants such as Claude) to accelerate code development, data QA/QC, documentation, and analysis, applying sound engineering judgment to validate and stress-test AI-assisted output. Develop correlations between geological, completion, operational, and financial variables and well- and asset-level performance. Perform ad-hoc analyses; troubleshoot data-quality issues across the business; proactively identify potential issues and recommend solutions. Serve as a liaison across Operations, Finance, IR, Reservoir/Asset teams, and IT/Data - bridging deeply technical work and business audiences. Monitor production, capital, and financial data for discrepancies and opportunities; recommend operational and process improvements. Contribute to data governance, code documentation, change-release process, and best practices; educate others in support of a data- and AI-first culture. Manage and engage in multiple initiatives simultaneously; independently prioritize tasks and eliminate roadblocks to meet target deadlines. Conduct business with the highest ethical standards; demonstrate decision-making that ensures the safety of all people associated with SM facilities. Other duties as assigned. Role-Specific Technical Knowledge & Skills Petroleum Engineering. Working command of production operations, artificial-lift applications, and fundamental reservoir engineering disciplines - decline curve analysis, rate/pressure transient analysis, volumetrics, recoveries, EURs, and recovery factors. Understanding of unconventional resource plays across multiple basins/operating regions and familiarity with reserves, economics, AFE, and capital-planning workflows. Ability to identify limitations and ranges of certainty in a data set and to relate reservoir, completion, and operational characteristics to well performance. Data Engineering & Analytics. Advanced ability to wrangle, pre-process, and feature-engineer data and to connect data from disparate sources to surface insights, data-quality issues, and variable correlations. Sound applied-statistics foundation; competence with machine-learning concepts and frameworks a plus. End-to-end pipeline design that is cost-effective and scalable; strong code documentation and change-management discipline. AI-Augmented Delivery. Ability to integrate AI tools into daily delivery to compress cycle time while retaining engineering ownership of correctness - treating AI output as a draft to be verified, not a final answer. Understands data-security and data-privacy implications of AI-assisted and cloud-based workflows and accounts for them appropriately. Computer/Software Applications Programming & Analytics: Advanced SQL and Python (pandas, numpy, and related data ecosystem); R or comparable a plus. Data Platforms & Architecture: Data virtualization via Denodo; Snowflake and/or Databricks; Palantir Foundry; relational database design; ETL/ELT (dbt, SSIS); cloud environments (Azure, AWS). Visualization & Reporting: Governed enterprise BI (Power BI, Spotfire, or Tableau) for refreshing dashboards, plus bespoke interactive tools built as self-contained HTML dashboards (D3, Plotly, Recharts) that run anywhere without a license or server. Advanced PowerPoint and Excel for executive and Board deliverables, produced to SM Energy brand standards. Development Tools: Git/GitHub, modern IDEs (VS Code, PyCharm), notebooks (Jupyter), and fast dependency/environment management (uv, Poetry, conda). Comfortable in the agentic developer loop - coding assistants such as Claude Code, Cursor, or GitHub Copilot working inside the IDE/terminal, not used only as a side chat. Agentic Delivery: Fluent in AI-assisted artifact creation - directing agentic tools (e.g., Claude) to build branded HTML dashboards, PowerPoint decks, and Excel models end to end from a specification, then refining them iteratively. Applies SM's visual standards programmatically ("brand-as-code") so output is board-ready by default, and exercises judgment over layout, data integrity, and narrative clarity rather than accepting first-pass output. AI-Augmented Development: Fluent in an AI-native analytics workflow - uses LLM assistants (e.g., Claude) and agentic tools to accelerate development, QA/QC, refactoring, and documentation, always validating output against engineering judgment. Can leverage the Model Context Protocol (MCP) to connect AI agents securely to enterprise data and tools (e.g., querying Denodo or Snowflake, drafting Office deliverables) and platform-native AI such as Snowflake Cortex and Power BI Copilot, keeping data security and governance front of mind. Petroleum Engineering Software: Aries, Wellview, and Spotfire; exposure to RTA/PTA and production-analysis tools; reservoir simulation and frac models a plus. Education Bachelor's degree required in Petroleum, Chemical, or Mechanical Engineering; Data Science; Computer Science; Statistics; or a related quantitative field. A dual foundation in engineering and computing/data is strongly preferred. Advanced degree a plus. Typical Experience Minimum of 6 years of relevant experience. Experience should span both petroleum engineering (production/operations, and/or reservoir) and hands-on data/analytics development. Demonstrated delivery of executive- or Board-facing analytical work is strongly preferred. SM Energy offers competitive compensation and benefits programs which include, but are not limited to, variable pay, health care coverage, retirement plan, protection coverage, time off and leave programs, training and development opportunities and a range of allowances connected to specific work situations. Details are available at Careers SM Energy Company (SM) (). Applications will be accepted on an ongoing basis until the position is filled.
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work - and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. Northrop Grumman is currently looking for a C/C++ Software Engineer (Level 3 or 4) to join our team of qualified, diverse individuals. As an integral part of our multi-discipline engineering team in the Advanced Weapons division, you will be on the forefront of developing next-generation solutions to protect technology for our nation's warfighters. The ideal candidate will be supporting all of our programs for implementing, testing, and extending our STE software. This position is required to be full-time, on-site in the Northridge, CA location. No remote/telework arrangement is available for this position. Relocation assistance, while not guaranteed, may be available. Roles and Responsibilities: A successful candidate will have the qualities and essential functional expertise with: Generate software documentation. Develop, implement, and maintain existing software for primarily Windows based desktop applications. Participate in all aspects of the software development lifecycle activities Use test equipment to troubleshoot software and hardware. Basic Qualifications for a C/C++ Software Engineer (Level 3): Bachelor's degree in a STEM discipline with 5+ years of revelant experience, or Master's degree in a STEM discipline with 3+ years of experience Strong professional experience developing software in C/C++ on Windows 10, 11, and Linux (preferably CentOS) Experience with MIL-STD-1553, TCP/IP, Serial, and Ethernet network communication protocols Experience in deriving software requirements from system requirements; working with SRSs, ICDs, CDRLs Current US Government DoW Secret clearance Basic Qualifications for a C/C++ Software Engineer (Level 4): Bachelor's degree in a STEM discipline and 8+ years of experience or Master's degree in a STEM discipline and 6 years of experience. Strong professional experience developing software in C/C++ on Windows 10, 11, and Linux (preferably CentOS) Experience with MIL-STD-1553, TCP/IP, Serial, and Ethernet network communication protocols Experience in deriving software requirements from system requirements; working with SRSs, ICDs, CDRLs Current US Government DoW Secret clearance Preferred Qualifications: Advanced hands on system troubleshooting and determining root cause analysis. Experience working in a Lab environment or production floor. Experience operating oscilloscopes, power meters, power supplies, signal generators, and spectrum analyzers Self-directed and able to manage your own time with little oversight Working experience in Atlassian tools such as Jira, Confluence, Bitbucket, etc. Experience with DOORS and/or EPLM. Experience working with hardware programmers such as JTAG and ability to set up test equipment to support software development Experience in other Object Oriented Programming languages like C# Experience in embedded systems design with preemptive, multitasking real-time operating systems Primary Level Salary Range: $114,000.00 - $171,000.00 Secondary Level Salary Range: $142,200.00 - $213,400.00 The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business. The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
10/28/2026
Full time
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work - and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history. Northrop Grumman is currently looking for a C/C++ Software Engineer (Level 3 or 4) to join our team of qualified, diverse individuals. As an integral part of our multi-discipline engineering team in the Advanced Weapons division, you will be on the forefront of developing next-generation solutions to protect technology for our nation's warfighters. The ideal candidate will be supporting all of our programs for implementing, testing, and extending our STE software. This position is required to be full-time, on-site in the Northridge, CA location. No remote/telework arrangement is available for this position. Relocation assistance, while not guaranteed, may be available. Roles and Responsibilities: A successful candidate will have the qualities and essential functional expertise with: Generate software documentation. Develop, implement, and maintain existing software for primarily Windows based desktop applications. Participate in all aspects of the software development lifecycle activities Use test equipment to troubleshoot software and hardware. Basic Qualifications for a C/C++ Software Engineer (Level 3): Bachelor's degree in a STEM discipline with 5+ years of revelant experience, or Master's degree in a STEM discipline with 3+ years of experience Strong professional experience developing software in C/C++ on Windows 10, 11, and Linux (preferably CentOS) Experience with MIL-STD-1553, TCP/IP, Serial, and Ethernet network communication protocols Experience in deriving software requirements from system requirements; working with SRSs, ICDs, CDRLs Current US Government DoW Secret clearance Basic Qualifications for a C/C++ Software Engineer (Level 4): Bachelor's degree in a STEM discipline and 8+ years of experience or Master's degree in a STEM discipline and 6 years of experience. Strong professional experience developing software in C/C++ on Windows 10, 11, and Linux (preferably CentOS) Experience with MIL-STD-1553, TCP/IP, Serial, and Ethernet network communication protocols Experience in deriving software requirements from system requirements; working with SRSs, ICDs, CDRLs Current US Government DoW Secret clearance Preferred Qualifications: Advanced hands on system troubleshooting and determining root cause analysis. Experience working in a Lab environment or production floor. Experience operating oscilloscopes, power meters, power supplies, signal generators, and spectrum analyzers Self-directed and able to manage your own time with little oversight Working experience in Atlassian tools such as Jira, Confluence, Bitbucket, etc. Experience with DOORS and/or EPLM. Experience working with hardware programmers such as JTAG and ability to set up test equipment to support software development Experience in other Object Oriented Programming languages like C# Experience in embedded systems design with preemptive, multitasking real-time operating systems Primary Level Salary Range: $114,000.00 - $171,000.00 Secondary Level Salary Range: $142,200.00 - $213,400.00 The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business. The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Summary: Have you ever dreamed of contributing to the development of groundbreaking technologies? Micron plans to invest more than $250 billion globally over the next decade in groundbreaking manufacturing and R&D, including fab expansion in the United States giving us the opportunity to bring in passionate team members to help us continue to be at the forefront of memory in the World! We have an outstanding opportunity for a high energy, tenacious, ambitious, result driven individual with a strong work ethic and integrity to join our Facilities Team in Boise, Idaho! Micron seeking a Life Safety & Fire Alarms Systems Engineer, to become part of a team that is helping shape the future of how the world uses information. T his is an outstanding opportunity to work at the forefront of technology while supporting the design, operation, and continuous improvement of critical life safety systems within world-class semiconductor manufacturing facilities. Responsibilities: Serve as a technical owner for fire alarm, mass notification, emergency communication, and life safety systems. Review of vendor provided design drawings and specifications for completeness, accuracy and adherence to all applicable design and safety standards and codes including NFPA 72, NFPA 70, NFPA 101, IFC, IBC, and FM Global requirements. Review system configurations, equipment layouts, and distribution routing to ensure functionality, life safety compliance, proper egress, maintainability, constructability, and alignment with P&IDs. Collaborate with multidisciplinary engineering, design, construction, Facilities, EHS, IT, Security, and vendor teams to achieve project objectives. Apply critical thinking and analytical problem-solving skills to Identify, develop, propose, and implement cost effective plans that improve overall equipment and system efficiencies. Support design, installation, testing, commissioning, and sustaining operations of life safety systems. Develop and maintain engineering, operations, and maintenance documentation. Troubleshoot system issues, analyze system performance data, and drive reliability improvements through continuous improvement initiatives. Minimum Qualifications Bachelor's degree in electrical, controls, or related engineering fields. 2 years of experience as a facilities life safety systems engineer within an industrial environment. Technical knowledge of fire detection, fire alarm, suppression, mass notification, emergency communication, and life safety systems. Experience with instrumentation and controls, including sensor integration, control panels, and I/O systems. Working knowledge of NFPA 72, NFPA 70, NFPA 101, NFPA 2001, IBC, IFC, and applicable FM Global requirements. Proficient in reviewing schematics, wiring diagrams, equipment specs, and network layouts. Preferred Qualifications 3+ Years of experience within the Semiconductor Industry. Familiarity with smart building technologies, including IoT-enabled fire detection, intelligent suppression systems, and integrated emergency communication platforms. Professional certifications such as NICET Fire Alarm Systems (Level III or IV preferred) or Certified Fire Protection Specialist (CFPS). Strong understanding of system interoperability and integration with facility-wide platforms such as SCADA, BMS, and DCIM systems. Experience using engineering and design tools such as AutoCAD, Revit, and Navisworks, Siemens, Notifier, Edwards, Simplex, Johnson Controls, or similar fire alarm platforms. Interest or experience in embracing agentic AI to improve engineering and operational processes. As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on . Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. To learn about your right to work click here. To learn more about Micron, please visit For US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at or 1- (select option ) Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.
10/28/2026
Full time
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Summary: Have you ever dreamed of contributing to the development of groundbreaking technologies? Micron plans to invest more than $250 billion globally over the next decade in groundbreaking manufacturing and R&D, including fab expansion in the United States giving us the opportunity to bring in passionate team members to help us continue to be at the forefront of memory in the World! We have an outstanding opportunity for a high energy, tenacious, ambitious, result driven individual with a strong work ethic and integrity to join our Facilities Team in Boise, Idaho! Micron seeking a Life Safety & Fire Alarms Systems Engineer, to become part of a team that is helping shape the future of how the world uses information. T his is an outstanding opportunity to work at the forefront of technology while supporting the design, operation, and continuous improvement of critical life safety systems within world-class semiconductor manufacturing facilities. Responsibilities: Serve as a technical owner for fire alarm, mass notification, emergency communication, and life safety systems. Review of vendor provided design drawings and specifications for completeness, accuracy and adherence to all applicable design and safety standards and codes including NFPA 72, NFPA 70, NFPA 101, IFC, IBC, and FM Global requirements. Review system configurations, equipment layouts, and distribution routing to ensure functionality, life safety compliance, proper egress, maintainability, constructability, and alignment with P&IDs. Collaborate with multidisciplinary engineering, design, construction, Facilities, EHS, IT, Security, and vendor teams to achieve project objectives. Apply critical thinking and analytical problem-solving skills to Identify, develop, propose, and implement cost effective plans that improve overall equipment and system efficiencies. Support design, installation, testing, commissioning, and sustaining operations of life safety systems. Develop and maintain engineering, operations, and maintenance documentation. Troubleshoot system issues, analyze system performance data, and drive reliability improvements through continuous improvement initiatives. Minimum Qualifications Bachelor's degree in electrical, controls, or related engineering fields. 2 years of experience as a facilities life safety systems engineer within an industrial environment. Technical knowledge of fire detection, fire alarm, suppression, mass notification, emergency communication, and life safety systems. Experience with instrumentation and controls, including sensor integration, control panels, and I/O systems. Working knowledge of NFPA 72, NFPA 70, NFPA 101, NFPA 2001, IBC, IFC, and applicable FM Global requirements. Proficient in reviewing schematics, wiring diagrams, equipment specs, and network layouts. Preferred Qualifications 3+ Years of experience within the Semiconductor Industry. Familiarity with smart building technologies, including IoT-enabled fire detection, intelligent suppression systems, and integrated emergency communication platforms. Professional certifications such as NICET Fire Alarm Systems (Level III or IV preferred) or Certified Fire Protection Specialist (CFPS). Strong understanding of system interoperability and integration with facility-wide platforms such as SCADA, BMS, and DCIM systems. Experience using engineering and design tools such as AutoCAD, Revit, and Navisworks, Siemens, Notifier, Edwards, Simplex, Johnson Controls, or similar fire alarm platforms. Interest or experience in embracing agentic AI to improve engineering and operational processes. As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on . Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. To learn about your right to work click here. To learn more about Micron, please visit For US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at or 1- (select option ) Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.