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Machine Learning Engineer 5 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. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 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. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 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. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 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. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description Job Description Job Description ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED The AI / RAG Software Engineer is responsible for designing, developing, deploying, and supporting Retrieval-Augmented Generation (RAG) solutions within a high-performance computing (HPC) Linux environment. In this role, the engineer works with Large Language Models (LLMs), LLM orchestration frameworks, knowledge retrieval systems, embedding models, and containerized architectures. The position requires strong expertise in Python, Kubernetes, Helm, CI/CD automation, and secure SI system development to deliver scalable, production-ready solutions in mission-critical environments. The annual base salary range for this role is $199,000-$235,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. , Required Skills Linux Systems Proficiency: Proven experience in Linux environments, including advanced CLI use for software development, troubleshooting, and system administration. Python Engineering: Recent hands-on software development experience using Python, supported by strong knowledge of software engineering design patterns and frameworks. Generative SI RAG Knowledge: Working knowledge of Generative SI technologies, including Large Language Models (LLMs), RAG architectures, embedding models, and vector databases. Containerization Technologies: Experience with Docker, Podman, or containerd for application packaging, deployment, and lifecycle management in production environments. Kubernetes Helm: Hands-on experience creating, configuring, and managing Kubernetes resources (Deployments, Services, ConfigMaps, Secrets, Ingresses, Operators) and authoring Helm charts. CI/CD Automation: Experience building and maintaining CI/CD pipelines using GitLab CI/CD, Flux CD, GitLab Runners, or equivalent tools. Observability Monitoring: Experience deploying and leveraging metrics, logging, and monitoring platforms including Prometheus and Grafana. DevSecOps SDLC: Understanding of software development lifecycle (SDLC) best practices, automated testing, security scanning, code quality analysis, and DevSecOps principles. Version Control: Proficiency with Git-based workflows, including branching models, code reviews, and pull/merge requests. Education: Bachelor's Degree in Data Analytics, Intelligence Studies, Computer Science, Finance/Economics, or a related discipline, PLUS 7 + years of specialized data analytics or financial intelligence experience OR Master's Degree in a related field, PLUS 5 + years of specialized analytical experience OR High School Diploma / GED, PLUS 9 + years of hands-on intelligence analysis, financial tracking, and data discovery experience in lieu of a degree. , Desired Skills Cloud Engineering: Familiarity with developing, deploying, troubleshooting, and sustaining mission applications within AWS Cloud environments. GPU Acceleration: Experience developing, running, and debugging GPU-enabled applications and hardware workloads. Machine Learning Frameworks: Hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow) and ML pipelines/platforms (e.g., KubeFlow, NeMo, PyTorch Lightning). Data Stores Search Engines: Experience working with SQL databases, Elasticsearch, and enterprise Vector databases. SI Inferencing Frameworks: Knowledge of high-performance SI inferencing and serving solutions such as vLLM, Nvidia NIM, or Triton Inference Server. Agile Tooling: Experience using the Atlassian suite (Jira, Confluence) for workflow management and documentation. , About Nyla Technology Solutions Nyla Technology Solutions delivers exceptional Artificial Intelligence (AI), Data Science, and Software Engineering services for the U.S. Government. Nyla embraces a forward-thinking and bold approach at every turn, earning us a solid reputation of technical trendsetters within the industry. We have a passion for developing solutions that have a quick and immediate impact on mission. Headquartered in Columbia, Maryland, our customers love how we tackle their most challenging problems and get things done. If you have the unique experience and expertise we are seeking, along with the desire and determination to invest your time and energy as a part of Nyla's team, Taking Care of All of You Nyla provides a top-of-market compensation and benefits package. And through our unique Nyla FLEX program, we custom tailor these benefits to best fit your lifestyle. The Nyla FLEX benefit program is designed to offer you flexibility in the 3 biggest areas of your life: your pay, your leave, and your schedule. PAY - Nyla starts with 4 weeks of Annual Leave plus 11 holidays and an additional day of Annual Leave for each year you're at the company. You have the flexibility to cash out your annual leave hours, opt out of other Nyla benefits, and/or arrange for additional hours on contract (over 40 hrs/week). There's even an option to earn 1.3 times your hourly rate once you work over 1880 hours on contract! LEAVE - Want to spend more time with the family? Want more time to travel the world? You can BUY additional annual leave for a total of 6 weeks of annual leave. That's up to 240 hours of leave plus 11 holidays! That's not even including paid anniversary leave! SCHEDULE - Does the traditional 40-hour workweek no longer fit your lifestyle? With Nyla FLEX, you have the freedom to scale down to 30-32 hours while still enjoying the top-notch Nyla benefits you know and love. It's flexibility that works for you without compromising the perks! WHAT ABOUT OTHER BENEFITS? Nyla's health care (medical, dental, and vision) is 100% covered by the company. We provide 10% 401k matching - with full vesting day 1! Our Professional Development offers $5,000 per year to be used towards fees, tuition, or time off for your continued growth. We even have a student loan repayment program and we provide 8 hours of volunteering annually so you can support your community, making your world a better place. To learn more about Nyla's culture and our exceptional benefit packages click here. Nyla is an equal opportunity employer.

This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance with polygraph. This is a hands-on technical role that requires an advanced software/systems engineering background. Coding/automation and design/architecture skills are required! The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at AWS. ProServe is a global organization of experts that help customers realize their desired business outcomes when utilizing AWS. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. As a Delivery Consultant, you will work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success throughout their cloud journey, providing technical expertise and best practices across the project lifecycle. You'll collaborate closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As an experienced technology professional, you will be responsible for: • Designing and implementing complex, scalable, and secure AWS solutions tailored to customer needs • Providing technical guidance and troubleshooting support throughout project delivery • Collaborating with stakeholders to gather requirements and propose effective migration strategies • Acting as a trusted advisor to customers on industry trends and emerging technologies • Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts About the team About AWS AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS- 7+ years of technical specialist, design and architecture experience - 5+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience - 7+ years of consulting, design and implementation of serverless distributed solutions experience - 5+ years of software development with object oriented language experience - Current, active US Government Security Clearance of TS/SCI with Polygraph PREFERRED QUALIFICATIONS- degree in advanced technology, or AWS Professional level certification - Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies - Experience in performance optimization and cost management for cloud environments - Experience communicating technical concepts to diverse audiences in pre-sales environments Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, MD, Jessup - 153 800.00 USD annually

Job Description Job Description Overview Location: Austin, TX (4 days in-office) Employment Type: Full-time Department: Engineering & Product RELOCATION ASSISTANCE PROVIDED As a Principal Machine Learning Engineer: You will play a key technical role on our Engineering team, identifying trends and insights across large data sets to discover where refined data or internal ML/AI models can improve our product outcomes and operations. As the second engineer joining our dedicated ML team, you will have outsized influence on our architecture, tooling, and ML strategy. Because we are a fast-growing, agile company, this is a true end-to-end role. You'll own researching, building, evaluating, and deploying your models to production, as well as monitoring them for quality and accuracy over time. We operate across data types including public, proprietary, and a large volume of image data. Because we currently operate without a dedicated Data Engineering team, you will also own the data layer for your models. In practice, that means you'll often be the first person to touch a given raw data source; you're comfortable going from an unrefined, previously unexplored data set through feature engineering and into a production ML model. You can expect roughly a 30% data pipeline / new dbt table building (lightweight, not heavy ETL) and 70% feature engineering, modeling, deployment, and monitoring split in your day-to-day work. You'll operate with a high degree of autonomy and serve as a trusted technical owner for business problems across the organization. Steadily is still early in our exploration of where AI/ML models can drive the biggest value, making this role ideal for engineers who thrive in ambiguous environments and want their technical work to translate directly into massive business impact. This is a full-time position based in our Austin, TX office (4 days a week in-office) . We are located near Mopac and W. Anderson Lane. Job Responsibilities Own the end-to-end ML lifecycle: Design, build, deploy, and evolve data sets and models with an emphasis on scalability, quality, and maintainability. Focus areas could include estimating property-level risk, accurately assessing costs, and using aerial image analysis or modeling techniques to identify attributes that feed into other models. Build and maintain the data layer : Build lightweight data pipelines and new dbt tables to get raw data model-ready, without owning heavy ETL infrastructure. Drive measurable business impact: Lead the exploration and implementation of new ML applications in our product ecosystem to better predict risk on a per-insured level and in aggregate across the entire portfolio. Write clean, maintainable code in our stack: We build on an event-driven architecture using Kafka, AWS (EKS), Python, Django/FastAPI, and Postgres, with a full CI/CD pipeline via GitHub Actions. You will set a high bar for engineering quality and architectural design within this ecosystem. Partner closely with Engineering, Product, Operations, and Business teams to design reliable solutions across systems and ensure your models are solving real-world problems. Provide excellent metrics and visibility into model quality, bias, and performance to assess how it's helping the business, ensuring a high bar of scientific rigor and evaluation. What we're looking for: Experienced: 5+ years experience applying Machine Learning methods to production problems. We expect you to be able to dive into a complex codebase without too much spin-up. Past experience as a team lead or owning end-to-end deployment is definitely a plus. Full-stack with data : You're comfortable starting from a raw, unrefined data source that no one has previously worked with, building the lightweight pipeline or dbt table to make it usable, and carrying it all the way through feature engineering, modeling, and deployment. Builder with a Business Mindset: You like the product-side of data and think about how to apply modeling and evaluation techniques to real-world problems. You aren't just interested in the research; you have thoughtful opinions about where the data leads and how to maximize the business impact of your work. Pragmatic: We prioritize impact and delivery. You balance speed and quality, making thoughtful trade-offs to solve problems effectively. You leverage off-the-shelf solutions (and foundational models) so we don't reinvent the wheel, but you understand when a custom solution is appropriate. Curious: You are not just an order-taker. You are curious about what makes the business tick and you learn the intricacies of how it runs. This results in strong intuition for when an analysis is wrong and leads you to suggest ideas and insights that nobody thought to ask for. You're not the type of engineer who wants fully fleshed-out specs thrown over the wall for you to implement. Nice to have: Actuarial experience, or experience applying models to risk evaluation and aggregation problems. Experience in computer vision and image analysis. Experience with dbt or similar modern data transformation tools. What We Offer: Compensation : Top of market salary + equity Time Off: 3 weeks PTO + 6 federal holidays Insurance: Medical, dental, vision, life, disability, HSA, FSA Retirement: 401(k) Perks: Free snacks, team lunches, collaborative office culture Why Join Steadily: Good company. Our founders have three successful startups under their belt and have recruited a stellar team to match. Top compensation . We pay at the top of the Austin market (see comp). Growth opportunity : We're an early-stage, fast-growing company where you'll wear a lot of hats and shape product decisions. Strong backing . We're growing fast, we manage over $20 billion in risk, and we're exceptionally well-funded. Culture : Steadily boasts a very unique culture that our teammates love. We call it like we see it and we're nothing if not candid. Plus, we love to have a good time. Check out our culture deck to learn what we're all about. Awards: We've been recognized both locally and nationally as a top place to work. Recently we were ranked 16th on Forbes' 2026 Best Startup Employers list, and 63rd on the prestigious Inc 5000 Fastest Growing Companies list. We've also been recognized as one of the Best Landlord Insurance Companies in 2026 by CNBC, a Top 2025 Startup in Newsweek, in Investopedia's Best Landlord Insurance Companies, and we won Austin Business Journal's Best Places to Work in 2025. We're excited to meet you!

Job Description Job Description About Applied Digital: At Applied Digital, we are the epicenter of AI innovation, crafting cutting-edge data center solutions tailored for the demands of high-performance computing. Designed from the ground up to support AI and machine learning workloads, our infrastructure is the backbone of tomorrow's technological advancements, including AI-driven video and generative platforms. We are: Forward-Thinkers: With a keen eye on current market trends and future innovations, we adapt swiftly and lead technological evolution. Resilient: We navigate complex challenges and emerge stronger, delivering robust and reliable solutions for industry pioneers. Innovative Designers: Leveraging the latest technologies, we create visionary solutions that redefine industry standards. At Applied Digital, we are committed to solving intricate problems, advancing business initiatives, maximizing operational efficiency, and reducing our carbon footprint. We are a team of resilient, forward-thinking innovators driving the AI revolution. Position Summary: Applied Digital is seeking a highly skilled Data Center UPS - Operational Subject Matter Expert (SME) to oversee and optimize the performance, reliability, and efficiency of our data center UPS infrastructure. This role provides deep technical expertise in UPS technologies (e.g., online double-conversion, line-interactive, standby, modular, battery-backed), power quality, battery management, and integration with generators, switchgear, and critical loads. The SME supports design, installation, commissioning, preventive/corrective maintenance, troubleshooting, training, and continuous improvement to minimize downtime and ensure compliance in high-availability environments like data centers, hospitals, telecom, industrial plants, and financial institutions. Key Responsibilities: Act as the go-to technical expert for all UPS-related matters, including system architecture, sizing, redundancy (e.g., N+1, 2N), runtime calculations, and fault analysis. Lead or support preventive maintenance, corrective repairs, battery testing/replacement, firmware updates, and major component replacements (e.g., rectifiers, inverters, static switches). Troubleshoot complex UPS failures, power quality issues (harmonics, transients, voltage sags), and integration problems with downstream equipment. Develop, review, and update technical documentation, standard operating procedures (SOPs), maintenance protocols, and training materials. Deliver hands-on training and certification programs for technicians, engineers, and operations staff on UPS operation, safety, and best practices. Perform root cause analysis (RCA) on incidents, recommend improvements, and contribute to reliability enhancements (e.g., predictive maintenance using monitoring software). Ensure compliance with industry standards and regulations (e.g., IEEE, NFPA 70, UL 1778, IEC 62040, OSHA, local electrical codes). Collaborate with cross-functional teams (e.g., electrical engineers, data center ops, vendors, procurement) on new UPS deployments, upgrades, capacity planning, and vendor evaluations. Analyze system performance data, KPIs (e.g., MTBF, availability, efficiency), and monitoring tools (e.g., SNMP, BMS integration) to drive optimizations. Provide emergency on-call support for critical UPS failures and participate in disaster recovery planning. Basic Qualifications: Experience: 5-7+ years of hands-on experience with uninterruptible power supply systems, including installation, service, and advanced troubleshooting in critical power environments. Education: Bachelor's degree in Electrical Engineering, Power Systems, Electronics, or related equivalent field experience preferred. Certifications: Preferred - Manufacturer-specific (e.g., Schneider APC, Eaton, Vertiv/Liebert, CyberPower); relevant industry certs like Certified Data Centre Professional (CDCP), NFPA 70E (electrical safety), or battery/UPS-specific training. Knowledge & Skills: In-depth expertise in UPS topologies, battery technologies (VRLA, lithium-ion, wet cell), power electronics, and paralleling/redundancy configurations. Strong understanding of electrical systems, power distribution, generators, ATS, and harmonics mitigation. Proficiency with UPS diagnostic tools, multimeters, oscilloscopes, thermal imaging, battery impedance testers, and monitoring software. Excellent problem-solving, analytical, and communication skills for technical reporting and stakeholder interaction. Ability to read/interpret electrical schematics, one-line diagrams, and OEM manuals. Please note that Applied Digital is currently unable to sponsor new applicants for employment authorization or provide immigration-related support for this position. This includes, but is not limited to, visa categories such as H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1, O-1, and any Employment Authorization Documents (EADs) or other work authorizations that require employer sponsorship. Physical Requirements: Able to remain in a seated position for an extended period and to lift and carry up to 15 lbs. (office manuals, case notebooks, case files, case materials, standard boxes, report binders, etc.) as needed. Note: The company has reviewed this job description to ensure that essential functions and basic duties have been included. It is intended to provide guidelines for job expectations and the employee's ability to perform the position described. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate. This document does not represent a contract of employment, and the company reserves the right to change this job description and/or assign tasks for the employee to perform, as the company may deem appropriate. This job description in no way states or implies that these are the only duties to be performed by the employee(s) incumbent in this position. Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the incumbents acknowledge that they possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. This document does not create an employment contract, implied or otherwise, other than an "at will" relationship. The company is an Equal Opportunity Employer, drug free workplace, and complies with ADA regulations as applicable.

Job Description Job Description An active or rein-statable TS/SCI with Polygraph security clearance is REQUIRED. Please do not apply if you currently do not possess this level of clearance. Are you an Principal AI/ML Engineer who is ready for a new challenge that will launch your career to the next level? Tired of being treated like a company drone? Tired of promised adventures during the hiring phase, then dropped off on a remote contract and never seen or heard from the mothership again? Our engineers were certainly tired of the same. At GliaCell our slogan is "We make It happen". We will immerse you in the latest technologies. We will develop and support your own personalized training program to continue your individual growth. We will provide you with work that matters with our mission focused customers, and surround you with a family of brilliant engineers. Culture isn't something you need to talk about if it just exists. If this sounds interesting to you, then we'd like to have a discussion regarding your next adventure! If you want to be a drone, this isn't the place for you. We Make It Happen! GliaCell Technologies focuses on Software & System Engineering in Enterprise and Cyber Security solution spaces. We excel at delivering stable and reliable software solutions using Agile Software Development principles. These provide us the capability to deliver a quick turn-around using interactive applications and the integration of industry standard software stacks. GliaCell's Enterprise capabilities include Full-Stack Application Development, Big Data, Cloud Technologies, Analytics, Machine Learning, AI, and DevOps Containerization. We also provide customer solutions in the areas of CND, CNE, and CNO by providing our customers with assessments and solutions in Threat Mitigation, Vulnerability Exposure, Penetration Testing, Threat Hunting, and Preventing Advanced Persistent Threat. We Offer: Long term job security Competitive salaries & bonus opportunities Challenging work you are passionate about Ability to work with some amazingly talented people Job Description: GliaCell is seeking a Principal AI/ML Engineer on one of our subcontracts. This is a full-time position offering the opportunity to support a U.S. Government customer. The mission is to provide technical expertise that assists in sustaining critical mission-related software and systems to a large government contract. Key Requirements: To be considered for this position you must have the following: U.S. Citizenship 10+ years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required. A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university. 7 additional years of machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree. Demonstrated abilities in software engineering and AI/ML model test and evaluation. Works well independently as well as on a team. Strong communication skills. Key Skills: You will design, create, test, and productize AI/ML algorithms to solve business challenges. The AI/ML models you create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. Should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation. Needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Need an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. You may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem-solving and communication skills. Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus. Location: Annapolis Junction, MD / Partial Telework (up to 16 hours per week) may be available for this position based on mission needs/available tasking at the discretion of leadership, after the individual has become fully acclimated to the duties and responsibilities of the position and has completed the necessary telework training. Salary Range: The salary range for this full-time position is $200,000 to $280,000. Our salary ranges are determined by position, level, skills, professional experience, relevant education and certifications. Your recruiter can share more about the specific salary range for your preferred position during the hiring process. Benefits: CareFirst Medical Coverage for Employee and Dependents Guardian Dental and Vision Coverage for Employee and Dependents Up to 25 Days of Paid Time Off Up to 40 hours of PTO Carryover 11 Federal Government Holidays Work From Home Opportunities 401K Company Contribution, Fully Vested Day 1 Discretionary, Certification, and Sign-On Bonus Potential Employee Referral Bonus Program Annual Professional Development 100% Premium Covered for Life & Disability Insurances Additional Voluntary Life Insurance Coverage Available Employee Assistance Program Travel Protection Program Financial Planning Assistance Bereavement and Jury Duty Leave Monthly Team and Family Events Technology Budget Global Entry Annual Swag Budget Learn more about GliaCell Technologies: To apply for this position, respond to this job posting and attach an updated resume for us to review. GliaCell Technologies, LLC is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status. Powered by JazzHR cDeBOm5dlB

Job Description Job Description Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. Become part of something big with Extreme! As a global networking leader, learn why there is no better time to join the Extreme team. Position details Title of position: Principal Machine Learning Engineer Position type: Full time Location: Seattle, WA Position reports to: Director of Software Systems Engineering Application deadline: Applications are being accepted on a rolling basis and this posting will remain open until filled. Work authorization: We are unable to sponsor or take over sponsorship of an employment visa, including H-1B visas, at this time About the Position: Position : Principal Machine Learning Engineer -Gen AI, Machine Learning, Graph ML, Big Data Experience : 10+ Years Seattle, WA - Hybrid Our AI Core group is pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship Extreme products while enabling entirely new offerings. Together, we are driving a fundamental shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Extreme, innovation is not just encouraged, it is expected. Advance with us and help shape the future of network intelligence. Required Skills & Expertise: Degree in mathematics/computer science or related discipline. 10+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations. 6+ years of experience in Python with an in-depth knowledge of its advanced features and libraries. Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI. Proficient in Docker, Kubernetes, and modern CI/CD practices. 4+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud). Experience as a mentor, tech lead or leading an engineering team. Preferred Qualifications: MS or PhD in Computer Science or equivalent experience in ML. Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.). Experience with NoSQL and document databases. Proven ability to handle big data, optimize workflows, and improve system performance. Come work with a team of highly talented engineers, and advance with us to achieve new heights every day! Equal Employment Opportunity Extreme Networks, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are committed to taking affirmative action to employ and advance in employment qualified protected veterans, including disabled veterans, recently separated veterans, active-duty wartime or campaign badge veterans, and Armed Forces service medal veterans. Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (for example, stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks. We encourage people from underrepresented groups to apply. This role offers a market competitive salary with an anticipated base compensation range of 150,000 to 200,000 USD. Actual compensation will depend on the selected candidate's experience, qualifications, skills, and work location. The posted range reflects the amount Extreme Networks reasonably and in good faith expects to pay upon hire. This range is determined using objective, gender neutral criteria based on skills, experience, responsibility, and working conditions. In addition to base pay, this role is eligible for a performance based bonus and the full benefits package described below. Benefits and total rewards: Extreme Networks offers a comprehensive benefits package. Specific benefits vary by country and may include: Medical, dental, and vision insurance Flexible work schedules and work-from-home opportunities where role permits Paid time off, including open time off in eligible markets and statutory leave in all markets Paid holidays in accordance with local practice Retirement savings programs, including RRSP matching in Canada Employee Stock Purchase Program, where eligible Employee assistance program Tuition reimbursement, where eligible Benefits eligibility is based on country of employment, role, and employment status. Complete benefits details will be provided during the interview process and in the formal offer of employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description About Agile Defense At Agile Defense we know that action defines the outcome and new challenges require new solutions. That's why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next. Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility-leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation's vital interests. Requisition #: 1945 Job Title: Principal Network Engineer III Location: Pocatello, ID. Onsite with option for five days per week or four days per week if working 10 hours per day. Clearance Level: Top Secret Clearance Required with SCI Eligibility and ability to obtain and maintain a CI Polygraph Required Certification(s): Cisco CCNA within six months of starting role Job Description The Network Engineer will be responsible for the design, deployment, testing, certification, patching, and troubleshooting of all network features, components, interoperability and application dependencies across data center environments. This includes switches, firewalls, load balancers, software-defined networking, and private cloud infrastructure. This position is onsite in Pocatello, ID, and requires an active Top Secret clearance at the time of application. We are seeking an Enterprise-level Network Engineer with six or more years of experience. The successful candidate will have or be able to obtain a CCNA, with strong preference for experience in Cisco ACI, NSO, and other advanced Cisco data center technologies. Responsibilities Design, implement, and provide ongoing support for networking infrastructure within and between data centers. Serve as an advanced subject matter expert for all data center network environments. Create and maintain network infrastructure for both bare metal and virtual machines, including LAN, WAN, VLAN, SDN, firewall, and load balancer configurations using OEM and third party tools such as NSX. Provision and configure required networking for servers, applications, and cloud services. Evaluate, improve, and maintain information security across the data center network infrastructure. Monitor, diagnose, and correct network issues; develop recovery processes for failures and performance bottlenecks. Provide real time alerts and implement proactive remediation, including redesigns or technology refreshes. Install, configure, test, and maintain system management tools for all network components. Ensure the highest levels of network availability, performance, redundancy, and resilience. Monitor and test application performance; identify bottlenecks and collaborate with developers on solutions. Maintain comprehensive security, backup, and redundancy strategies. Develop and maintain automation scripts to improve operational efficiency, including automated provisioning of addresses and VLANs for IaaS. Participate in the design of information and operational support systems. Provide final tier support for complex network issues. Liaise with vendors and IT personnel for troubleshooting, upgrades, and solution design. Generate real time dashboards and reporting on network performance, availability, trends, and resource utilization. Maintain accurate and up to date technical documentation, including inventory, patch levels, system configurations, access controls, and credentials. Continually transition knowledge to government staff through training and best practice guidance. Education and Years of Experience Bachelor's degree 6 years of relavant experience Bachelor's degree preferred but one year of experience may be substituted for each year of education. Required Skills Active and current Top-Secret clearance required with SCI eligibility and ability to obtain and maintain a CI Polygraph Ability to pass and maintain a CI Polygraph during employment Cisco CCNA passed withing 6-months of start date Preferred Skills CCNP or DevNet Associate certificate Cisco ACI experience Multi Site Orchestrator (MSO) experience Network Assurance Engine (NAE) experience Network Services Orchestrator (NSO) experience Nexus Insights experience Digital Network Architecture Center (DNAC) experience In addition, Agile Defense invests in its employees beyond just compensation. Agile's benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, short-term and long-term Disability, Retirement and Learning and Development opportunities as well as other optional benefit elections. Our Core Values Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together. What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are. Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do. Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated. Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support. Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task. Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges. Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success. Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We're seeking a Software Development Engineer to join the AWS Quick RAG team, working on cutting-edge retrieval-augmented generation technology that powers Amazon Quick Suite's intelligent document processing and search capabilities. You'll design and build scalable ingestion pipelines that handle multi-modal content (PDF, audio, video, tables) using computer vision and machine learning, optimize system performance for millions of documents, and collaborate across teams to deliver features that directly impact customer experience. This role offers the opportunity to work with modern AWS technologies including Bedrock, ECS, and DynamoDB while solving complex distributed systems challenges at scale. Key job responsibilities As a Software Development Engineer, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this role, you will collaborate closely with your team to influence our overall strategy and define the team's road map. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment. A day in the life As a Software Development Engineer on the AWS Quick RAG team, you'll start your day reviewing system metrics and performance dashboards to ensure our ingestion pipelines are processing millions of documents efficiently. You'll spend time coding-whether building new features for multi-modal content processing, optimizing retrieval algorithms, or debugging complex distributed systems issues. Throughout the day, you'll collaborate with applied scientists on machine learning model integration, participate in design reviews with partner teams, and contribute to architectural decisions that shape how customers interact with their data. You'll also mentor junior engineers through code reviews and technical discussions, balancing hands-on development with the opportunity to influence the technical direction of a product used by thousands of enterprise customers. About the team The AWS Quick RAG team is responsible for building and maintaining the intelligent document processing backbone of Amazon Quick Suite. We develop scalable ingestion pipelines that handle millions of documents across multiple modalities-PDF, audio, video, tables, and more-using advanced computer vision and machine learning techniques. Our work directly powers Quick Suite's search and retrieval capabilities, enabling enterprise customers to unlock insights from their data. We're a collaborative, innovation-driven team that values technical excellence, operational rigor, and customer obsession, working closely with applied scientists, product managers, and partner teams across AWS to deliver features that transform how organizations interact with their information. BASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 143 400.00 USD annually

This Jobot Job is hosted by: Craig Rosecrans Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume. Salary: $200,000 - $275,000 per year A bit about us: We are partnering with a rapidly growing, venture-backed technology company operating at the intersection of Artificial Intelligence and cybersecurity to hire an AI Solutions Architect focused on Federal customers. This is not a traditional Solutions Architect position where you simply deliver presentations and hand opportunities back to Engineering. We are looking for someone who can architect, build, deploy, demonstrate, and troubleshoot real AI solutions while working directly with mission owners across the Intelligence Community, Department of Defense, DHS, and civilian federal agencies. You will serve as the technical lead throughout the customer journey-from initial discovery and architecture discussions through proof-of-value, deployment, integration, and technical win. The right person will be equally comfortable writing Python, deploying Kubernetes into an air-gapped environment, building an AI proof of concept, whiteboarding an architecture, and presenting the solution to senior government stakeholders. Why join us? You'll join a well-funded, rapidly scaling company building technology in one of the most important emerging areas of cybersecurity: protecting AI systems themselves. The company has recently completed a significant new funding round and is continuing to expand its engineering, product, and federal organizations. The opportunity offers: Fully remote work within the United States Significant exposure to cutting-edge AI and cybersecurity technology Direct involvement with important federal AI initiatives High technical autonomy and ownership Opportunity to work closely with Product, Research, Engineering, and customers Flexible paid time off Company holidays Home-office and connectivity support Dedicated learning and development funding for training, certifications, conferences, and industry events If you're a deeply technical Solutions Architect who understands Federal missions, AI/ML, cloud-native infrastructure, and security-and you want to help solve the emerging challenge of securing AI systems-we'd love to speak with you. Job Details What You'll Do Lead Federal Technical Engagements: Partner with federal Account Directors to lead technical strategy across complex government opportunities. Conduct discovery with mission owners, AI/ML engineers, security teams, architects, and executive stakeholders. Understand customers' AI initiatives, architectures, data pipelines, infrastructure, security requirements, and compliance constraints. Translate loosely defined mission challenges into clearly scoped technical evaluations and proof-of-value engagements. Establish measurable success criteria, timelines, technical requirements, and exit conditions. Serve as a trusted technical advisor and provide candid guidance around where the platform is-and is not-the right solution. Architect & Deploy Real Solutions: Architect and deploy an enterprise AI security platform across both connected SaaS and fully disconnected/air-gapped environments. Package and transfer container images, Helm charts, dependencies, and supporting artifacts into environments with limited or no internet connectivity. Deploy and administer Kubernetes-based environments utilizing technologies such as: Kubernetes Docker Helm Private container registries OpenShift VMware / Proxmox AWS, including government and restricted environments Troubleshoot deployment, networking, integration, and infrastructure issues during customer evaluations and initial implementations. Work directly with SDKs and APIs to build meaningful integrations into customer environments. Build AI Demonstrations & Proofs of Concept: Develop mission-focused AI applications and technical demonstrations involving: Large Language Models Agentic AI Computer Vision Model inference Retrieval/RAG architectures AI/ML pipelines Demonstrate how AI systems can be attacked, compromised, or manipulated-and how those systems can be protected. Integrate AI security capabilities throughout the ML lifecycle, including model scanning, CI/CD pipelines, application security, runtime detection, and response. Build credible demonstrations that resonate with engineers and mission owners rather than relying on canned sales demos. Advise on AI Security: Help federal customers understand how to secure: AI/ML models LLM-powered applications AI agents Data and inference pipelines Model supply chains AI infrastructure Production AI workloads Apply established security concepts and frameworks including: MITRE ATLAS OWASP Top 10 for LLM Applications NIST AI Risk Management Framework Adversarial machine learning concepts and attack methodologies Communicate & Influence: Deliver live technical demonstrations, architecture sessions, whiteboard discussions, and executive briefings. Present effectively to audiences ranging from ML engineers and data scientists to cybersecurity leaders and senior executives. Create technical evaluation reports, reference architectures, deployment documentation, and integration guides. Represent the organization at federal engagements, conferences, webinars, and industry events. Translate lessons learned in the field into reusable demonstrations, technical enablement, and feedback for Product, Research, and Engineering. What We're Looking For We are looking for a highly technical, customer-facing architect who has actually worked inside federal environments and understands the realities of deploying sophisticated technology into government infrastructure. Ideal candidates will bring: 5+ years of experience in Solutions Architecture, Solutions Engineering, Applied AI Engineering, ML Engineering, or a similar customer-facing technical role. Direct experience supporting federal customers across the Intelligence Community, DoD, DHS, or civilian agencies. Experience operating within federal missions-not simply selling technology into federal accounts. Strong hands-on Python development skills. Practical experience building and integrating modern AI/ML systems. Experience with technologies and concepts such as: PyTorch Hugging Face ONNX LLM APIs Model inference RAG Agentic AI architectures AI/ML pipelines Strong hands-on experience with Docker, Kubernetes, and Helm. Experience deploying applications into restricted, disconnected, or air-gapped environments. Understanding of MLOps, CI/CD, and the lifecycle of models from development through production. Working knowledge of cybersecurity and AI security concepts. Strong technical presentation and communication skills. Ability to take an ambiguous customer problem and independently turn it into an executable technical plan. Ability and willingness to travel for customer engagements and industry events. Especially Valuable Experience: Additional experience in any of the following areas would be highly desirable: Active Top Secret or higher-level security clearance. Supporting AI/ML programs in classified environments. Securing production AI or machine-learning systems. AI/LLM red teaming or adversarial machine learning. AI security or AI evaluation tooling. Model formats and AI supply-chain security, including: ONNX SafeTensors GGUF Pickle-based serialization AWS GovCloud or other government cloud environments. OpenShift and private Kubernetes environments. Federal cybersecurity or compliance frameworks. Certifications such as Kubernetes, AWS, Azure, CISSP, or Security+. Public technical work including GitHub repositories, Hugging Face projects, conference presentations, open-source contributions, or technical writing. The Type of Person Who Will Thrive Here: This organization moves quickly and operates much more like a high-growth technology company than a traditional government contractor. We're looking for someone who enjoys solving problems without a perfectly defined playbook. You should be someone who can walk into an ambiguous federal mission problem, ask the right questions, architect a solution, stand up the environment, write the integration, demonstrate it live, troubleshoot what breaks, and explain the outcome to both engineers and executives. Intellectual curiosity is especially important. The strongest candidates are typically people who are constantly experimenting-building side projects, maintaining home labs, testing new AI frameworks, contributing to open source, publishing technical content, or simply teaching themselves technologies because they want to understand how they work. Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot's policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions. Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. Information collected and processed as part of your Jobot candidate profile, and any job applications, resumes . click apply for full job details

We're seeking a Software Development Engineer to join the AWS Quick RAG team, working on cutting-edge retrieval-augmented generation technology that powers Amazon Quick Suite's intelligent document processing and search capabilities. You'll design and build scalable ingestion pipelines that handle multi-modal content (PDF, audio, video, tables) using computer vision and machine learning, optimize system performance for millions of documents, and collaborate across teams to deliver features that directly impact customer experience. This role offers the opportunity to work with modern AWS technologies including Bedrock, ECS, and DynamoDB while solving complex distributed systems challenges at scale. Key job responsibilities As a Software Development Engineer, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this role, you will collaborate closely with your team to influence our overall strategy and define the team's road map. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment. A day in the life As a Software Development Engineer on the AWS Quick RAG team, you'll start your day reviewing system metrics and performance dashboards to ensure our ingestion pipelines are processing millions of documents efficiently. You'll spend time coding-whether building new features for multi-modal content processing, optimizing retrieval algorithms, or debugging complex distributed systems issues. Throughout the day, you'll collaborate with applied scientists on machine learning model integration, participate in design reviews with partner teams, and contribute to architectural decisions that shape how customers interact with their data. You'll also mentor junior engineers through code reviews and technical discussions, balancing hands-on development with the opportunity to influence the technical direction of a product used by thousands of enterprise customers. About the team The AWS Quick RAG team is responsible for building and maintaining the intelligent document processing backbone of Amazon Quick Suite. We develop scalable ingestion pipelines that handle millions of documents across multiple modalities-PDF, audio, video, tables, and more-using advanced computer vision and machine learning techniques. Our work directly powers Quick Suite's search and retrieval capabilities, enabling enterprise customers to unlock insights from their data. We're a collaborative, innovation-driven team that values technical excellence, operational rigor, and customer obsession, working closely with applied scientists, product managers, and partner teams across AWS to deliver features that transform how organizations interact with their information. BASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 143 400.00 USD annually

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Director of Data Science, are you ready to lead the charge in transforming a major enterprise through the power of Generative AI, LLMs, and autonomous agent ecosystems? We are seeking a visionary Director of Data Science to architect and scale our next-generation AI capabilities. In this role, you will lead a high-performing team responsible for building reusable, horizontal AI platforms and solutions that drive enterprise-wide automation, innovation, and strategic differentiation. You possess the agility to navigate rapidly shifting AI paradigms, the architectural vision to design scalable systems from ideation to production-grade performance, and the leadership to bridge the gap between cutting-edge research and core business value. If you thrive at the intersection of AI strategy, technical execution, and organizational transformation, we want you to lead our future. What you will do: Acts as an enterprise AI thought leader and strategic advisor, shaping how the organization leverages generative AI, LLMs, and agentic workflows to drive competitive advantage and market differentiation. Influences business, data, and technology executives to invest in, scale, and future-proof enterprise-wide horizontal AI capabilities through active participation in strategy, planning, and budgeting. Directs and empowers a team of AI/Data Scientists and engineers to build and deploy scalable LLM applications, RAG pipelines, and autonomous agent systems in a fast-paced, agile environment. Architecturally guides the team from ideation to performant production solutions, optimizing the AI lifecycle from prompt engineering and context management to model evaluation and inference cost-efficiency. Champions the creation of modular, reusable horizontal AI capabilities and services that can be leveraged horizontally across disparate business units to solve complex challenges. Partners closely with Enterprise Architecture and IT to establish modern AI infrastructure, tooling pipelines, and scalable cloud/on-premise deployment standards. Ensures all AI models, agentic workflows, and generative solutions strictly adhere to emerging AI safety guidelines, model risk management (MRM) frameworks, data governance, and regulatory compliance. Identifies and secures strategic resource needs, ranging from next-gen LLM API integrations and specialized 3rd-party toolsets to specialized hardware and talent investments. Builds, inspires, and scales a world-class team of AI talent through intentional recruiting, technical mentorship, coaching, and performance management. Ensures risks associated with AI operations (e.g., hallucinations, data leakage, security vulnerabilities, and autonomous agent drift) are effectively identified, measured, monitored, and controlled. What you have: 8+ years of progressive experience in machine learning, advanced data science, and AI development-with a strong recent emphasis on deploying Generative AI, LLMs, or agentic systems to production-OR an Advanced Degree (Master's or PhD) in Computer Science, AI, Data Science, or a quantitative STEM field with 6+ years of relevant experience. 3+ years of direct people leadership experience, building, managing, and inspiring high-performing technical teams in rapidly evolving tech landscapes. Proven track record of architecting and delivering scalable, high-performance horizontal AI platforms or reusable capabilities that drive cross-enterprise transformation. Exceptional strategic agility and flexibility, with a demonstrated history of successfully pivoting technical strategies and teams in response to rapid paradigm shifts in the AI ecosystem. Deep technical background in modern AI frameworks and methodologies (e.g., LangChain, LlamaIndex, vector databases, fine-tuning, RAG architectures, prompt engineering patterns, and multi-agent orchestration). Comprehensive understanding of AI governance, risk mitigation (guardrails, prompt injection defense, alignment), model risk policies, and compliance expectations for automated and autonomous systems. Exceptional executive communication skills; a proven track record of translating complex AI architectures, ROI metrics, and technical roadmaps into compelling narratives for Senior Executive Management and non-technical stakeholders. Compensation range: The salary range for this position is: $189,370 - $361,950 USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Application deadline: Nov 6, 2026 The Frontier ADC team is at the forefront of delivering the AWS GenAI and Agentic AI service portfolio to our customers in GovCloud and isolated environments. We are dedicated to pushing the boundaries of what is possible in this rapidly evolving field, leveraging the power of cloud computing and the latest advancements in artificial intelligence and machine learning technologies. With a focus on expanding Frontier AI services across GovCloud and isolated regions, driving automation investments, and delivering innovative solutions, we are at the forefront of modernization. Our teams are innovating new ways of building massively scalable distributed systems and delivering the next generation of cloud computing across the GenAI and Agentic AI service portfolio. We support the GenAI and Agentic AI service portfolio including services like Amazon Bedrock, Amazon Quick, Amazon Bedrock AgentCore, and Kiro. We are seeking a Software Development Engineer II who can think big and simplify solutions to complex problems, all while ensuring our customers continue to have the best experience possible! A successful Software Development Engineer II joining the team will be an innovator, building solutions and working closely with Amazon's largest and most demanding government customers to address their specific needs across a suite of Frontier AI services in GovCloud and isolated environments. They will drive the resolution of technical issues and work diligently to improve the customer experience. This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance. The position further requires that, after start, the selected candidate obtain and maintain an active TS/SCI security clearance with polygraph or commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities The ideal candidate will: • Be great fun to work with. Our company credo is "Work hard. Have fun. Make history". The right candidate will love what they do and instinctively know how to make work fun. • Have strong Linux & Networking Fundamentals. The ideal candidate will have deep experience working with Linux, preferably in a large scale, distributed environment. You understand networking technology and how servers and networks inter-relate. You regularly take part in deep-dive troubleshooting and conduct technical post-mortem discussions to identify the root cause of complex issues. • Have strong software and systems skills. The ideal candidate will have deep experience working with systems in a large scale, distributed environment. You understand networking technology and how servers and networks inter-relate. You are comfortable facilitating deep-dive troubleshooting and leading technical post-mortem discussions to identify the root cause of complex issues. • Love to solve problems. The ideal candidate will love leading teams to solve difficult technical problems related to AWS service builds and operations in GovCloud and isolated environments. You have a solid understanding of systems design, operations, automation, and process improvement. • Think Big. The ideal candidate will work on projects building and deploying solutions across GovCloud and isolated regions. You will strive to build a culture to improve and streamline processes to allow for work on a massive scale. A day in the life As a Software Development Engineer II in Frontier ADC, you will build innovative solutions, expand services into GovCloud and isolated regions, and improve our operations to provide resiliency and the best experience for our customers. You influence technical strategy and architectural decisions within the team and with partner teams and make data-driven decisions. Successful candidates will be expected to show leadership on strong Bias for Action, Invent and Simplify, Insist on the Highest Standards, and Deliver Results. You will develop, build, and operate AWS Frontier AI services that enable customers to leverage generative AI and agentic capabilities in secure environments. Our engineering teams support services running in GovCloud and isolated regions, creating unique engineering challenges and opportunities for innovation. The Frontier ADC team is responsible for diving deep to resolve operational challenges, innovating to automate operational tasks, building solutions for our customers, supporting execution of various security campaigns (blocked software, host patching), and parity programs. As a Software Development Engineer II you will: • Work cross-functionally to foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues. • Love to code. Whether it's building tools in Java or solving complex system problems in Python, the ideal candidate will love using technology to solve problems. • Think Big. The ideal candidate will build and deploy solutions across thousands of devices. You will strive to improve and streamline processes to allow for work on a massive scale. About the team Why AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Mentorship and Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. BASIC QUALIFICATIONS- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - Current, active US Government Security Clearance of Top Secret with SCI eligibility or above PREFERRED QUALIFICATIONS- Bachelor's degree in computer science or equivalent - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - 3+ years of software development engineer or related occupational experience - 2+ years of Object Oriented Design experience Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CO, Denver - 143 400.00 USD annually

Future Java, Data, and AI Professionals - Start Your Tech Career With a Process If you are serious about launching a career in tech, do not rely only on random applications, scattered tutorials, or hope. The candidates who stand out usually have current skills, strong projects, interview confidence, and a clear story about the value they can bring. That is especially important in competitive entry-level and junior hiring. Since 2010, we've helped thousands of candidates land full-time jobs at tech leaders like Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Paypal, Banking, Wayfair, Client, Client and hundreds more with Job offers of $95k to $154k. Synergisticit focuses on closing the gap between your tech skills and what employers want now. We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics with limited or no job experience Jobseekers who had layoffs due to Downsizing and want to get in demand tech stack Professionals seeking a career switch to tech Candidates with career gaps or lacking real-world experience Individuals looking to boost their skill portfolio for better job prospects Computer Science grads with limited or no job experience Students who recently finished their Bachelor's or Master's programs Those struggling to land interviews despite having experience Please check below links: Event videos (OCW, JavaOne, Gartner): Explore JOPP: Reviews: please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates Technical Skills or Experience? Which one is important to get a Job? SynergisticIT is looking for candidates interested in entry-level software programming, Java full-stack development, Python/Java development, DevOps, data analysis, BI, data engineering, data science, machine learning, and AI programming. This opportunity is ideal for recent graduates, bootcamp graduates, career changers, laid-off candidates, and job seekers with limited experience. SynergisticIT JOPP is good for candidates because it is built around job readiness and placement-focused preparation. It helps candidates strengthen technical skills, build project proof, improve resume positioning, prepare for interviews, and approach the job market with a structured plan. Start your tech career with a process-not guesswork. Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req. Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume.

Application deadline: Nov 5, 2026 The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle. Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. Key job responsibilities As an experienced technology professional, you will be responsible for: - Designing and implementing complex, scalable, and secure AWS solutions tailored to customer needs - Providing technical guidance and troubleshooting support throughout project delivery - Collaborating with stakeholders to gather requirements and propose effective migration strategies - Acting as a trusted advisor to customers on industry trends and emerging technologies - Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts About the team Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture - Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth - We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. BASIC QUALIFICATIONS- 3+ years of cloud architecture and solution implementation experience - Knowledge of the primary aws services (ec2, elb, rds, route53 & s3) - Experience implementing AWS services in a variety of distributed computing environments - Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field - Current, active US Government Security Clearance of TS/SCI with Polygraph PREFERRED QUALIFICATIONS- 5+ years of IT implementation experience - degree in advanced technology, or AWS Professional level certification - Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies - Knowledge of security and compliance standards including HIPAA and GDPR - Experience and technical expertise (design and implementation) in cloud computing technologies - Experience leading the design, development and deployment of business software at scale or recent hands-on technology infrastructure, network, compute, storage, and virtualization experience - Experience in performance optimization and cost management for cloud environments Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, MO, St. Louis - 131 600.00 USD annually USA, VA, Arlington - 131 600.00 USD annually USA, VA, Herndon - 131 600.00 USD annually