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Boeing
Senior Software Engineer - Lab Provisioning & Integration
Boeing Saint Louis, Missouri
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. The Boeing Company is currently seeking a Senior Software Engineer - Lab Provisioning & Integration in Berkeley, MO. You will apply sophisticated engineering principles and deep expertise to architect and deliver highly scalable, secure, and resilient lab environments supporting critical multi-program integration and test activities. You will lead initiatives requiring creativity and ingenuity, influence organizational technical direction, and provide leadership and mentorship in cloud infrastructure, automation, and DevSecOps. This role carries significant responsibility for ensuring technical excellence, delivering innovative solutions to complex challenges, and acting as a primary technical liaison with internal teams and external stakeholders. Position Responsibilities: Advanced Lab Environment Leadership: Apply specialized knowledge and insights to architect, provision, and optimize complex lab/test environments on-premises and across cloud platforms (Azure, AWS) using Infrastructure as Code (Terraform, Ansible). Establish and standardize best practices. Integration Testing Architecture: Lead the design and continuous improvement of enterprise-wide automated integration testing workflows involving multiple program segments, ensuring comprehensive, data-driven feedback and rapid resolution of cross-segment integration issues. Strategic Deployment Pipeline Ownership: Drive innovation in deployment mechanisms and pipelines for physical and virtual systems, ensuring scalability, security, repeatability, and operational excellence aligned with long-term organizational objectives. Data-Driven Insight & Decision Making: Establish advanced processes for collecting, analyzing, and interpreting performance, stability, and integration data to deliver strategic recommendations that support organizational goals. Technical Leadership & Mentorship: Serve as a recognized technical leader and resource. Mentor and guide engineers across projects, promote engineering rigor and best practices, facilitate knowledge sharing, and contribute to a high-performance culture. Security & Compliance Leadership: Lead integration of security principles and ensure compliance with relevant industry standards (CIS, NIST, SOC 2, FedRAMP). Promote adoption of security tools and standards across DevSecOps processes. Cross-Organizational Liaison: Represent Boeing as a trusted technical advisor on advanced programs; lead coordination with senior personnel and external partners on complex technical issues. This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location option. Basic Qualifications (Required Skills/ Experience): Position requires an Active Secret US Security Clearance and ability to obtain Top Secret post-start for which the US Government requires US Citizenship Bachelor's Degree 9+ years of relevant professional experience or equivalent combination of education and experience Knowledge of CICD process tools such as GITLab, Azure DevOps, Jenkins etc Experience with light scripting (e.g., Python, PowerShell, Bash) to automate routine tasks, data flows between systems, and improve system reliability Experience leading people and complex projects Preferred Qualifications (Desired Skills/Experience): Bachelor of Science degree from an accredited course of study in engineering, engineering technology (includes manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science and 9+ years of related work experience OR Bachelor's Degree and 13+ years of directly related work experience OR 17+ years of related, relevant experience Extensive experience with observability platforms (Prometheus, Grafana, ELK, CloudWatch) to deliver actionable monitoring insights Advanced experience architecting, deploying, and maintaining production-grade Kubernetes clusters (EKS, AKS) Proven knowledge of DevSecOps security frameworks and cloud security best practices Deep expertise provisioning and leading complex lab/test environments both on-premises and in public cloud (Azure, AWS) Exceptional problem-solving skills, technical judgment, and the ability to work under minimal supervision Effective communication skills with experience liaising between technical teams, leadership, and external customers Certifications like Certified Kubernetes Administrator (CKA), AWS Certified DevOps Engineer, Azure DevOps Engineer Expert Experience leading GitOps workflows and tools (Argo CD, Flux) Knowledge of secrets management solutions (HashiCorp Vault, Azure Key Vault) Familiarity with service mesh technologies such as Istio, Linkerd Demonstrated track record mentoring engineers and leading technical initiatives Experience in Infrastructure as Code (IaC) and CI/CD environments Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) Conflict of Interest: Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process. Drug Free Workplace: Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies. CodeVue Coding Challenge: To be considered for this position you will be required to complete a technical assessment as part of the selection process. Failure to complete the assessment will remove you from consideration. Pay & Benefits: At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities. The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Summary Pay Range: $160,650 - $217,350 Applications for this position will be accepted until Nov. 20, 2026 Export Control Requirements: This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. 120.62 is required. "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee. Export Control Details: US based job, US Person required Education Bachelor's Degree or Equivalent Required Relocation This position offers relocation based on candidate eligibility. Security Clearance This position requires an active U.S. Secret Security Clearance (U.S. Citizenship Required). (A U.S. Security Clearance that has been active in the past 24 months is considered active) Visa Sponsorship Employer will not sponsor applicants for employment visa status. Shift This position is for 1st shift Equal Opportunity Employer: Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
11/14/2026
Full time
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. The Boeing Company is currently seeking a Senior Software Engineer - Lab Provisioning & Integration in Berkeley, MO. You will apply sophisticated engineering principles and deep expertise to architect and deliver highly scalable, secure, and resilient lab environments supporting critical multi-program integration and test activities. You will lead initiatives requiring creativity and ingenuity, influence organizational technical direction, and provide leadership and mentorship in cloud infrastructure, automation, and DevSecOps. This role carries significant responsibility for ensuring technical excellence, delivering innovative solutions to complex challenges, and acting as a primary technical liaison with internal teams and external stakeholders. Position Responsibilities: Advanced Lab Environment Leadership: Apply specialized knowledge and insights to architect, provision, and optimize complex lab/test environments on-premises and across cloud platforms (Azure, AWS) using Infrastructure as Code (Terraform, Ansible). Establish and standardize best practices. Integration Testing Architecture: Lead the design and continuous improvement of enterprise-wide automated integration testing workflows involving multiple program segments, ensuring comprehensive, data-driven feedback and rapid resolution of cross-segment integration issues. Strategic Deployment Pipeline Ownership: Drive innovation in deployment mechanisms and pipelines for physical and virtual systems, ensuring scalability, security, repeatability, and operational excellence aligned with long-term organizational objectives. Data-Driven Insight & Decision Making: Establish advanced processes for collecting, analyzing, and interpreting performance, stability, and integration data to deliver strategic recommendations that support organizational goals. Technical Leadership & Mentorship: Serve as a recognized technical leader and resource. Mentor and guide engineers across projects, promote engineering rigor and best practices, facilitate knowledge sharing, and contribute to a high-performance culture. Security & Compliance Leadership: Lead integration of security principles and ensure compliance with relevant industry standards (CIS, NIST, SOC 2, FedRAMP). Promote adoption of security tools and standards across DevSecOps processes. Cross-Organizational Liaison: Represent Boeing as a trusted technical advisor on advanced programs; lead coordination with senior personnel and external partners on complex technical issues. This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location option. Basic Qualifications (Required Skills/ Experience): Position requires an Active Secret US Security Clearance and ability to obtain Top Secret post-start for which the US Government requires US Citizenship Bachelor's Degree 9+ years of relevant professional experience or equivalent combination of education and experience Knowledge of CICD process tools such as GITLab, Azure DevOps, Jenkins etc Experience with light scripting (e.g., Python, PowerShell, Bash) to automate routine tasks, data flows between systems, and improve system reliability Experience leading people and complex projects Preferred Qualifications (Desired Skills/Experience): Bachelor of Science degree from an accredited course of study in engineering, engineering technology (includes manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science and 9+ years of related work experience OR Bachelor's Degree and 13+ years of directly related work experience OR 17+ years of related, relevant experience Extensive experience with observability platforms (Prometheus, Grafana, ELK, CloudWatch) to deliver actionable monitoring insights Advanced experience architecting, deploying, and maintaining production-grade Kubernetes clusters (EKS, AKS) Proven knowledge of DevSecOps security frameworks and cloud security best practices Deep expertise provisioning and leading complex lab/test environments both on-premises and in public cloud (Azure, AWS) Exceptional problem-solving skills, technical judgment, and the ability to work under minimal supervision Effective communication skills with experience liaising between technical teams, leadership, and external customers Certifications like Certified Kubernetes Administrator (CKA), AWS Certified DevOps Engineer, Azure DevOps Engineer Expert Experience leading GitOps workflows and tools (Argo CD, Flux) Knowledge of secrets management solutions (HashiCorp Vault, Azure Key Vault) Familiarity with service mesh technologies such as Istio, Linkerd Demonstrated track record mentoring engineers and leading technical initiatives Experience in Infrastructure as Code (IaC) and CI/CD environments Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) Conflict of Interest: Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process. Drug Free Workplace: Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies. CodeVue Coding Challenge: To be considered for this position you will be required to complete a technical assessment as part of the selection process. Failure to complete the assessment will remove you from consideration. Pay & Benefits: At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities. The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Summary Pay Range: $160,650 - $217,350 Applications for this position will be accepted until Nov. 20, 2026 Export Control Requirements: This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. 120.62 is required. "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee. Export Control Details: US based job, US Person required Education Bachelor's Degree or Equivalent Required Relocation This position offers relocation based on candidate eligibility. Security Clearance This position requires an active U.S. Secret Security Clearance (U.S. Citizenship Required). (A U.S. Security Clearance that has been active in the past 24 months is considered active) Visa Sponsorship Employer will not sponsor applicants for employment visa status. Shift This position is for 1st shift Equal Opportunity Employer: Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
S&P Global
Machine Learning Engineer II
S&P Global New York, New York
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Kensho is S&P Global's hub for AI innovation and transformation. With expertise in machine learning, natural language processing, and data discovery, we develop and deploy novel solutions to innovate and drive progress at S&P Global and its customers worldwide. Kensho's solutions and research focus on business and financial generative AI applications, agents, data retrieval APIs, data extraction, and much more. At Kensho, we hire talented people and give them the autonomy and support needed to build amazing technology and products. We collaborate using our teammates' diverse perspectives to solve hard problems. Our communication with one another is open, honest, and efficient. We dedicate time and resources to explore new ideas, but always rooted in engineering best practices. As a result, we can innovate rapidly to produce technology that is scalable, robust, and useful. The DRIVE Team at Kensho is focused on designing and deploying production-grade machine learning systems that power our next-generation agentic search pipelines. We specialize in building robust retrieval systems, scalable embedding infrastructure, and tightly integrated LLM pipelines that leverage unstructured data sources. Our mission is to make complex unstructured data easily discoverable and actionable by building intelligent, retrieval-driven systems that enhance enterprise search, question answering, deep research, report generation, and knowledge discovery experiences across S&P Global platforms. We are seeking a mid-level Machine Learning Engineer to help develop and scale RAG systems across the company. This is a hands-on, full-lifecycle ML role with a strong emphasis on retrieval models, LLM orchestration, and system-level thinking. Kensho states that the anticipated base salary range for the position is 140k - 180k. In addition, this role is eligible for an annual incentive bonus and equity plans. At Kensho, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. What You'll Do: Design and implement end-to-end RAG pipelines that integrate proprietary chunking algorithms, embedding models, vector databases, and data retrieval agents Build and optimize retrieval systems over large-scale proprietary datasets using advanced embedding techniques Develop LLM-based solutions that orchestrate retrieval, generation, and ranking to deliver high-quality, context-aware responses Investigate and solve challenges in vector search, chunking and indexing strategies, unstructured data retrieval evaluation, and GraphRAG Work closely with Product and Design teams to build ML-based solutions that enhance user experiences and meet business objectives Collaborate closely with the ML Operations team to create automated solutions for managing the entire ML systems lifecycle, from initial technical design to seamless implementation Who You'll Need: Bachelor's degree or higher in Computer Science, Engineering, or a related field. 3+ years of significant, hands-on industry experience with machine learning, natural language processing (NLP), information retrieval systems and large-scale text processing, including designing, shipping, and maintaining production systems Strong programming skills in Python, with a working knowledge of data processing tools and ML frameworks such as PyTorch, Transformers, and HuggingFace Experience working with machine learning libraries/frameworks for Large Language Model (LLM) orchestration, such as Langchain, LLamaIndex, etc. Proven experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation. Experience working with vector databases (e.g., PostgreSQL/PGVector, OpenSearch, Pinecone) and understanding of similarity search techniques and vector indexing algorithms Demonstrated effective coding, documentation, collaboration, and communication habits Strong problem-solving skills and a proactive approach to addressing challenges Ability to adapt to a fast-paced and dynamic work environment Technologies We Love: ML: PyTorch, Transformers, HuggingFace, LangChain Tools/Toolkits: Claude Code, Weights & Biases, OpenSearch, PostgreSQL/PGVector, LiteLLM Techniques : Agentic Search, Prompt Engineering, Information Retrieval, Data Embedding, AI agent evaluation Deployment: Airflow, Docker, Kubernetes, Jenkins, AWS, Github Action At Kensho, we pride ourselves on providing top-of-market benefits, including: Medical, Dental, and Vision insurance 100% company paid premiums Unlimited Paid Time Off 26 weeks of 100% paid Parental Leave (paternity and maternity) 401(k) plan with 6% employer matching Generous company matching on donations to non-profit charities Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences Plentiful snacks, drinks, and regularly catered lunches Dog-friendly office (CAM office) Bike sharing program memberships Compassion leave and elder care leave Mentoring and additional learning opportunities Opportunity to expand professional network and participate in conferences and events Recruitment Fraud Alert: If you receive an email from a domain or any other regionally based domains, it is a scam and should be reported to . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, "pre-employment training" or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here . We are an equal opportunity employer that welcomes future Kenshins with all experiences and perspectives. Kensho is headquartered in Cambridge, MA, with an additional office location in New York City. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
11/13/2026
Full time
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Kensho is S&P Global's hub for AI innovation and transformation. With expertise in machine learning, natural language processing, and data discovery, we develop and deploy novel solutions to innovate and drive progress at S&P Global and its customers worldwide. Kensho's solutions and research focus on business and financial generative AI applications, agents, data retrieval APIs, data extraction, and much more. At Kensho, we hire talented people and give them the autonomy and support needed to build amazing technology and products. We collaborate using our teammates' diverse perspectives to solve hard problems. Our communication with one another is open, honest, and efficient. We dedicate time and resources to explore new ideas, but always rooted in engineering best practices. As a result, we can innovate rapidly to produce technology that is scalable, robust, and useful. The DRIVE Team at Kensho is focused on designing and deploying production-grade machine learning systems that power our next-generation agentic search pipelines. We specialize in building robust retrieval systems, scalable embedding infrastructure, and tightly integrated LLM pipelines that leverage unstructured data sources. Our mission is to make complex unstructured data easily discoverable and actionable by building intelligent, retrieval-driven systems that enhance enterprise search, question answering, deep research, report generation, and knowledge discovery experiences across S&P Global platforms. We are seeking a mid-level Machine Learning Engineer to help develop and scale RAG systems across the company. This is a hands-on, full-lifecycle ML role with a strong emphasis on retrieval models, LLM orchestration, and system-level thinking. Kensho states that the anticipated base salary range for the position is 140k - 180k. In addition, this role is eligible for an annual incentive bonus and equity plans. At Kensho, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. What You'll Do: Design and implement end-to-end RAG pipelines that integrate proprietary chunking algorithms, embedding models, vector databases, and data retrieval agents Build and optimize retrieval systems over large-scale proprietary datasets using advanced embedding techniques Develop LLM-based solutions that orchestrate retrieval, generation, and ranking to deliver high-quality, context-aware responses Investigate and solve challenges in vector search, chunking and indexing strategies, unstructured data retrieval evaluation, and GraphRAG Work closely with Product and Design teams to build ML-based solutions that enhance user experiences and meet business objectives Collaborate closely with the ML Operations team to create automated solutions for managing the entire ML systems lifecycle, from initial technical design to seamless implementation Who You'll Need: Bachelor's degree or higher in Computer Science, Engineering, or a related field. 3+ years of significant, hands-on industry experience with machine learning, natural language processing (NLP), information retrieval systems and large-scale text processing, including designing, shipping, and maintaining production systems Strong programming skills in Python, with a working knowledge of data processing tools and ML frameworks such as PyTorch, Transformers, and HuggingFace Experience working with machine learning libraries/frameworks for Large Language Model (LLM) orchestration, such as Langchain, LLamaIndex, etc. Proven experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation. Experience working with vector databases (e.g., PostgreSQL/PGVector, OpenSearch, Pinecone) and understanding of similarity search techniques and vector indexing algorithms Demonstrated effective coding, documentation, collaboration, and communication habits Strong problem-solving skills and a proactive approach to addressing challenges Ability to adapt to a fast-paced and dynamic work environment Technologies We Love: ML: PyTorch, Transformers, HuggingFace, LangChain Tools/Toolkits: Claude Code, Weights & Biases, OpenSearch, PostgreSQL/PGVector, LiteLLM Techniques : Agentic Search, Prompt Engineering, Information Retrieval, Data Embedding, AI agent evaluation Deployment: Airflow, Docker, Kubernetes, Jenkins, AWS, Github Action At Kensho, we pride ourselves on providing top-of-market benefits, including: Medical, Dental, and Vision insurance 100% company paid premiums Unlimited Paid Time Off 26 weeks of 100% paid Parental Leave (paternity and maternity) 401(k) plan with 6% employer matching Generous company matching on donations to non-profit charities Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences Plentiful snacks, drinks, and regularly catered lunches Dog-friendly office (CAM office) Bike sharing program memberships Compassion leave and elder care leave Mentoring and additional learning opportunities Opportunity to expand professional network and participate in conferences and events Recruitment Fraud Alert: If you receive an email from a domain or any other regionally based domains, it is a scam and should be reported to . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, "pre-employment training" or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here . We are an equal opportunity employer that welcomes future Kenshins with all experiences and perspectives. Kensho is headquartered in Cambridge, MA, with an additional office location in New York City. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
Braze
Staff Machine Learning Engineer, ML Platform
Braze Austin, Texas
This job is with Braze, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity - inside and outside our organization. To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success. Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you. WHAT YOU'LL DO Braze is seeking a Staff Machine Learning Engineer to join our Predictive and Generative AI (PGAI) team. The team's mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions. We run those solutions as production systems at global scale, from the distributed pipelines that train models for each customer to the high-throughput APIs that serve predictions into our messaging systems across multiple regions. You will own the platform underneath, and you will make deploying, operating, and scaling ML at Braze fast, safe, and efficient. As the Staff Engineer on the team, you will: Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership WHO YOU ARE 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making Bonus: Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray ML platform tooling such as MLflow or another model registry, feature stores, or ML observability Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes) Operating under compliance regimes such as SOX or HIPAA Customer engagement, personalization, or marketing technology domain experience For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company. WHAT WE OFFER Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country at here . More details on benefits plans will be provided if you receive an offer of employment. From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as: Competitive compensation that may include equity Retirement and Employee Stock Purchase Plans Flexible paid time off Comprehensive benefit plans covering medical, dental, vision, life, and disability Family services that include fertility benefits and equal paid parental leave Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend A curated in-office employee experience, designed to foster community, team connections, and innovation Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching Employee Resource Groups that provide supportive communities within Braze Collaborative, transparent, and fun culture recognized as a Great Place to Work ABOUT BRAZE Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences. The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 "Best of Marketing and Digital Advertising Software Product" in 2025. Braze was also named a 2025 Best Companies To Work For by U.S. News and World Report, a 2025 America's Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology by Great Place To Work , among other accolades. Braze is also proudly certified as a Great Place to Work in the U.S., the UK, Australia, and Singapore. The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo. BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER At Braze, we strive to create equitable growth and opportunities inside and outside the organization. Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience - regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you. We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we'd love to meet you OUR AI-POWERED BRAZE RECRUITMENT PROCESS At Braze, we're committed to a fair and transparent candidate experience. To help our recruitment teams focus on what matters most - the person behind each application - we use AI-assisted tools at certain stages of our recruitment process. This includes using AI to analyze the experience, skills and qualifications in your application materials to help with screening and prioritizing candidates. Such screening may amount to a form of solely automated decision-making. We also use AI for administrative support, like scheduling and recording interviews and summarizing interview notes. Our recruiting teams remain responsible for all hiring decisions and are involved throughout the process. . click apply for full job details
11/13/2026
Full time
This job is with Braze, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity - inside and outside our organization. To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success. Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you. WHAT YOU'LL DO Braze is seeking a Staff Machine Learning Engineer to join our Predictive and Generative AI (PGAI) team. The team's mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions. We run those solutions as production systems at global scale, from the distributed pipelines that train models for each customer to the high-throughput APIs that serve predictions into our messaging systems across multiple regions. You will own the platform underneath, and you will make deploying, operating, and scaling ML at Braze fast, safe, and efficient. As the Staff Engineer on the team, you will: Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership WHO YOU ARE 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making Bonus: Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray ML platform tooling such as MLflow or another model registry, feature stores, or ML observability Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes) Operating under compliance regimes such as SOX or HIPAA Customer engagement, personalization, or marketing technology domain experience For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company. WHAT WE OFFER Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country at here . More details on benefits plans will be provided if you receive an offer of employment. From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as: Competitive compensation that may include equity Retirement and Employee Stock Purchase Plans Flexible paid time off Comprehensive benefit plans covering medical, dental, vision, life, and disability Family services that include fertility benefits and equal paid parental leave Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend A curated in-office employee experience, designed to foster community, team connections, and innovation Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching Employee Resource Groups that provide supportive communities within Braze Collaborative, transparent, and fun culture recognized as a Great Place to Work ABOUT BRAZE Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences. The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 "Best of Marketing and Digital Advertising Software Product" in 2025. Braze was also named a 2025 Best Companies To Work For by U.S. News and World Report, a 2025 America's Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology by Great Place To Work , among other accolades. Braze is also proudly certified as a Great Place to Work in the U.S., the UK, Australia, and Singapore. The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo. BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER At Braze, we strive to create equitable growth and opportunities inside and outside the organization. Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience - regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you. We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we'd love to meet you OUR AI-POWERED BRAZE RECRUITMENT PROCESS At Braze, we're committed to a fair and transparent candidate experience. To help our recruitment teams focus on what matters most - the person behind each application - we use AI-assisted tools at certain stages of our recruitment process. This includes using AI to analyze the experience, skills and qualifications in your application materials to help with screening and prioritizing candidates. Such screening may amount to a form of solely automated decision-making. We also use AI for administrative support, like scheduling and recording interviews and summarizing interview notes. Our recruiting teams remain responsible for all hiring decisions and are involved throughout the process. . click apply for full job details
Sr Associate Engineer/Engineer, IT Software
American Airlines Fort Worth, Texas
Intro Are you ready to explore a world of possibilities, both at work and duringyour time off? Join our American Airlines family, and you'll travel the world, grow your expertise and become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board! Why you'll love this job As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. The Software domain refers to the area within Information Technology that focuses on the development, deployment, management, and maintenance of software applications that support business processes and user needs. This includes development, application lifecycle management, requirement analysis, QA, security & compliance, and maintaining the applications and infrastructure. What you'll do As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations. Writes, tests, and documents technical work products (e.g., code, scripts, processes) according to organizational standards and practices Consistently produces good quality technical work products that are clear, concise, tested, and easily understood by others Efficiently debugs design-time and run-time problems and effectively identifies problems in dependencies or caused by interactions with other services Designs new implementations and provides enhancements to existing architectures, maintaining reliability, resiliency, security, and performance Identifies and corrects issues with system components affecting operational reliability, stability and performance based on observable telemetry Understands and follows secure coding practices to avoid known potential vulnerabilities and actively looks for vulnerabilities during code reviews Identifies opportunities for automation that improve team performance and raises them to the team Consistently identifies and capitalizes on opportunities for simplification All you'll need for success Minimum Qualifications- Education & Prior Job Experience Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 1+ years of experience designing, developing, and implementing large-scale solutions in production environments Preferred Qualifications- Education & Prior Job Experience Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training Airline Industry experience Skills, Licenses & Certifications Experience with the following technologies: Programming Languages: Java, Python, C#, Javascript/Typescript Frameworks: Spring/SpringBoot, FastAPI Front End Technologies: Angular/React Deployment Technologies: Kubernetes, Docker Source Control: GitHub, Azure DevOps CICD: GitHub Actions, Azure DevOps Data management: PostgreSQL, MongoDB, Redis Integration/APIs Technologies: Kafka, REST, GraphQL Cloud Providers such as Azure and AWS Test Automation: Selenium, TestNG, Postman, SonarQube, Cypress, JUnit/NUnit/PyTest, Cucumber, Playwright, Wiremock/Mockito/Moq Ability to concisely convey ideas verbally, in writing, in code, and in diagrams Experience in Agile methodologies, such as SCRUM Experience in DevOps Toolchain methodologies, including Continuous Integration and Continuous Deployment Familiarity with modern AI development practices, including spec-driven development, AI- assited coding tools, and critical review of AI-generated code What you'll get Feel free to take advantage of all that American Airlines has to offer: Travel Perks: Ready to explore the world? You, your family and your friends can reach 365 destinations on more than 6,800 daily flights across our global network. Health Benefits: On day one, you'll have access to your health, dental, prescription and vision benefits to help you stay well. And that's just the start, we also offer virtual doctor visits, flexible spending accounts and more. Wellness Programs: We want you to be the best version of yourself - that's why our wellness programs provide you with all the right tools, resources and support you need. 401(k) Program: Available upon hire and, depending on the workgroup, employer contributions to your 401(k) program are available after one year. Additional Benefits: Other great benefits include our Employee Assistance Program, pet insurance and discounts on hotels, cars, cruises and more Feel free to be yourself at American From the team members we hire to the customers we serve, inclusion and diversity are the foundation of the dynamic workforce at American Airlines. Our 20+ Team Member Business Resource Groups are focused on connecting our team members to our customers, suppliers, communities and shareholders, helping team members reach their full potential and creating an inclusive work environment to meet and exceed the needs of our diverse world. Are you ready to feel a tremendous sense of pride and satisfaction as you do your part to keep the largest airline in the world running smoothly as we care for people on life's journey? Feel free to be yourself at American.
11/13/2026
Full time
Intro Are you ready to explore a world of possibilities, both at work and duringyour time off? Join our American Airlines family, and you'll travel the world, grow your expertise and become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board! Why you'll love this job As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. The Software domain refers to the area within Information Technology that focuses on the development, deployment, management, and maintenance of software applications that support business processes and user needs. This includes development, application lifecycle management, requirement analysis, QA, security & compliance, and maintaining the applications and infrastructure. What you'll do As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations. Writes, tests, and documents technical work products (e.g., code, scripts, processes) according to organizational standards and practices Consistently produces good quality technical work products that are clear, concise, tested, and easily understood by others Efficiently debugs design-time and run-time problems and effectively identifies problems in dependencies or caused by interactions with other services Designs new implementations and provides enhancements to existing architectures, maintaining reliability, resiliency, security, and performance Identifies and corrects issues with system components affecting operational reliability, stability and performance based on observable telemetry Understands and follows secure coding practices to avoid known potential vulnerabilities and actively looks for vulnerabilities during code reviews Identifies opportunities for automation that improve team performance and raises them to the team Consistently identifies and capitalizes on opportunities for simplification All you'll need for success Minimum Qualifications- Education & Prior Job Experience Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 1+ years of experience designing, developing, and implementing large-scale solutions in production environments Preferred Qualifications- Education & Prior Job Experience Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training Airline Industry experience Skills, Licenses & Certifications Experience with the following technologies: Programming Languages: Java, Python, C#, Javascript/Typescript Frameworks: Spring/SpringBoot, FastAPI Front End Technologies: Angular/React Deployment Technologies: Kubernetes, Docker Source Control: GitHub, Azure DevOps CICD: GitHub Actions, Azure DevOps Data management: PostgreSQL, MongoDB, Redis Integration/APIs Technologies: Kafka, REST, GraphQL Cloud Providers such as Azure and AWS Test Automation: Selenium, TestNG, Postman, SonarQube, Cypress, JUnit/NUnit/PyTest, Cucumber, Playwright, Wiremock/Mockito/Moq Ability to concisely convey ideas verbally, in writing, in code, and in diagrams Experience in Agile methodologies, such as SCRUM Experience in DevOps Toolchain methodologies, including Continuous Integration and Continuous Deployment Familiarity with modern AI development practices, including spec-driven development, AI- assited coding tools, and critical review of AI-generated code What you'll get Feel free to take advantage of all that American Airlines has to offer: Travel Perks: Ready to explore the world? You, your family and your friends can reach 365 destinations on more than 6,800 daily flights across our global network. Health Benefits: On day one, you'll have access to your health, dental, prescription and vision benefits to help you stay well. And that's just the start, we also offer virtual doctor visits, flexible spending accounts and more. Wellness Programs: We want you to be the best version of yourself - that's why our wellness programs provide you with all the right tools, resources and support you need. 401(k) Program: Available upon hire and, depending on the workgroup, employer contributions to your 401(k) program are available after one year. Additional Benefits: Other great benefits include our Employee Assistance Program, pet insurance and discounts on hotels, cars, cruises and more Feel free to be yourself at American From the team members we hire to the customers we serve, inclusion and diversity are the foundation of the dynamic workforce at American Airlines. Our 20+ Team Member Business Resource Groups are focused on connecting our team members to our customers, suppliers, communities and shareholders, helping team members reach their full potential and creating an inclusive work environment to meet and exceed the needs of our diverse world. Are you ready to feel a tremendous sense of pride and satisfaction as you do your part to keep the largest airline in the world running smoothly as we care for people on life's journey? Feel free to be yourself at American.
Principal Java & GCP Solution Architect
HTC Global Services Inc Detroit, Michigan
Principal Java & GCP Solution Architect Principal Java and GCP Solution Architect who can bring both deep technical expertise and thought leadership to complex client engagements. This role requires a hands-on architect who can design modern Java microservices, shape cloud-native strategy on GCP, guide engineering teams, and serve as a trusted technical voice with senior client stakeholders. This is not a documentation-only architecture position-the successful candidate must remain close to implementation and be able to turn architectural direction into practical delivery outcomes. Join our growing Detroit-area team in a strategic Principal Java & GCP Solution Architect role. You'll work a hybrid / onsite /remote combin while remaining available for onsite collaboration as needed with clients, delivery teams, and technical leadership across the local Michigan area. What You Will Do Lead the architecture, design, and implementation of modern Java-based applications using cloud-native and microservices patterns. Translate business requirements into practical architectural blueprints aligned with enterprise standards and long-term strategy. Provide technical thought leadership across ongoing and future client engagements. Assess existing application landscapes and recommend modernization, migration, and optimization strategies. Design secure, scalable, resilient, observable, and high-performing distributed systems. Define application, integration, API, data, deployment, and operational architecture. Establish API-first strategies using REST, GraphQL, gRPC, and event-driven patterns. Design asynchronous and event-driven solutions using technologies such as Kafka or RabbitMQ. Guide engineering teams in the use of Java 11+, Spring Boot, microservices, containers, Kubernetes, and cloud-native design patterns. Lead architecture reviews, technical assessments, proofs of concept, and technology evaluations. Establish reusable architecture standards, reference patterns, engineering guidelines, and technical governance. Collaborate with developers, DevOps engineers, QA teams, security teams, product leaders, and business stakeholders. Provide technical guidance throughout design, development, testing, deployment, and production support. Guide containerization and orchestration strategies using Docker and Kubernetes, preferably Google Kubernetes Engine. Define CI/CD, GitOps, and infrastructure-as-code approaches using tools such as Jenkins, ArgoCD, Git, and Terraform. Design observability frameworks covering logs, metrics, traces, alerts, dashboards, and production diagnostics. Evaluate emerging technologies and determine where they can provide practical business and engineering value. Mentor senior developers, technical leads, and architects. Present architecture recommendations, trade-offs, risks, and decisions to senior technical and business stakeholders. Identify technical risks, dependencies, architectural gaps, and remediation strategies. Ensure architectural decisions support maintainability, security, performance, scalability, reliability, and cost efficiency. Required Qualifications Extensive experience designing and delivering enterprise Java applications. Deep expertise in Java 11 or later and Spring Boot. Proven experience architecting microservices and distributed systems. Strong production-level architecture experience with Google Cloud Platform. Experience designing and deploying applications using GCP cloud-native services. Strong hands-on knowledge of Docker and Kubernetes. Experience with Google Kubernetes Engine or comparable enterprise Kubernetes platforms. Strong understanding of RESTful APIs and API-first architecture. Experience with one or more additional integration patterns or technologies: GraphQL gRPC Event-driven architecture Asynchronous messaging Experience with Kafka, RabbitMQ, or comparable messaging technologies. Strong knowledge of scalability, resilience, fault tolerance, performance, security, and observability. Experience with SQL and NoSQL databases, including distributed-system data modeling. Experience with MongoDB, Cassandra, or comparable NoSQL platforms. Knowledge of API gateways and service-mesh technologies. Experience with Istio, Linkerd, or comparable service-mesh platforms. Experience with CI/CD and DevOps toolchains. Working knowledge of Jenkins, GitOps, ArgoCD, Terraform, or comparable tools. Strong experience designing logging, monitoring, metrics, and distributed-tracing solutions. Experience with one or more of the following: OpenTelemetry Prometheus Grafana ELK Stack Dynatrace Jaeger Zipkin Proven architecture-governance and technical-leadership experience. Strong client-facing communication and presentation skills. Ability to explain complex technical concepts, options, risks, and trade-offs to both technical and nontechnical audiences. Demonstrated ability to influence technical strategy and guide teams without relying solely on formal authority. Preferred Qualifications Experience leading complex cloud-modernization or monolith-to-microservices programs. Experience supporting multiple enterprise or client engagements. Consulting or systems-integration experience. GCP Professional Cloud Architect certification. Experience establishing enterprise architecture standards or cloud-native reference architectures. Experience designing highly available, high-volume, or mission-critical platforms. Experience conducting architecture assessments and technology-selection initiatives. Experience mentoring architects and senior engineers. Public speaking, technical writing, internal technology leadership, or architecture-community participation. Ideal Candidate The ideal candidate is more than a senior Java developer who has moved into architecture. You have personally owned architecture decisions for complex enterprise platforms and can explain how those decisions improved business, delivery, reliability, or operational outcomes. You remain technically close enough to implementation to guide developers, review designs, evaluate code-level implications, troubleshoot difficult issues, and challenge assumptions. At the same time, you are comfortable presenting to senior client stakeholders and influencing long-term technology strategy. You know how to introduce modern technologies thoughtfully. You evaluate business value, operational complexity, risk, scalability, and long-term maintainability rather than adopting tools simply because they are new. What Success Looks Like Success in this role includes: Building credibility as a trusted technical advisor Improving the quality and consistency of architectural decisions Establishing reusable Java and GCP architecture patterns Helping teams deliver scalable and reliable cloud-native solutions Identifying architecture risks before they become delivery or production issues Strengthening engineering practices across client engagements Contributing technical expertise that expands and deepens client relationships What Makes HTC A Great Place To Build Your Future HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies. At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks. Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
11/13/2026
Full time
Principal Java & GCP Solution Architect Principal Java and GCP Solution Architect who can bring both deep technical expertise and thought leadership to complex client engagements. This role requires a hands-on architect who can design modern Java microservices, shape cloud-native strategy on GCP, guide engineering teams, and serve as a trusted technical voice with senior client stakeholders. This is not a documentation-only architecture position-the successful candidate must remain close to implementation and be able to turn architectural direction into practical delivery outcomes. Join our growing Detroit-area team in a strategic Principal Java & GCP Solution Architect role. You'll work a hybrid / onsite /remote combin while remaining available for onsite collaboration as needed with clients, delivery teams, and technical leadership across the local Michigan area. What You Will Do Lead the architecture, design, and implementation of modern Java-based applications using cloud-native and microservices patterns. Translate business requirements into practical architectural blueprints aligned with enterprise standards and long-term strategy. Provide technical thought leadership across ongoing and future client engagements. Assess existing application landscapes and recommend modernization, migration, and optimization strategies. Design secure, scalable, resilient, observable, and high-performing distributed systems. Define application, integration, API, data, deployment, and operational architecture. Establish API-first strategies using REST, GraphQL, gRPC, and event-driven patterns. Design asynchronous and event-driven solutions using technologies such as Kafka or RabbitMQ. Guide engineering teams in the use of Java 11+, Spring Boot, microservices, containers, Kubernetes, and cloud-native design patterns. Lead architecture reviews, technical assessments, proofs of concept, and technology evaluations. Establish reusable architecture standards, reference patterns, engineering guidelines, and technical governance. Collaborate with developers, DevOps engineers, QA teams, security teams, product leaders, and business stakeholders. Provide technical guidance throughout design, development, testing, deployment, and production support. Guide containerization and orchestration strategies using Docker and Kubernetes, preferably Google Kubernetes Engine. Define CI/CD, GitOps, and infrastructure-as-code approaches using tools such as Jenkins, ArgoCD, Git, and Terraform. Design observability frameworks covering logs, metrics, traces, alerts, dashboards, and production diagnostics. Evaluate emerging technologies and determine where they can provide practical business and engineering value. Mentor senior developers, technical leads, and architects. Present architecture recommendations, trade-offs, risks, and decisions to senior technical and business stakeholders. Identify technical risks, dependencies, architectural gaps, and remediation strategies. Ensure architectural decisions support maintainability, security, performance, scalability, reliability, and cost efficiency. Required Qualifications Extensive experience designing and delivering enterprise Java applications. Deep expertise in Java 11 or later and Spring Boot. Proven experience architecting microservices and distributed systems. Strong production-level architecture experience with Google Cloud Platform. Experience designing and deploying applications using GCP cloud-native services. Strong hands-on knowledge of Docker and Kubernetes. Experience with Google Kubernetes Engine or comparable enterprise Kubernetes platforms. Strong understanding of RESTful APIs and API-first architecture. Experience with one or more additional integration patterns or technologies: GraphQL gRPC Event-driven architecture Asynchronous messaging Experience with Kafka, RabbitMQ, or comparable messaging technologies. Strong knowledge of scalability, resilience, fault tolerance, performance, security, and observability. Experience with SQL and NoSQL databases, including distributed-system data modeling. Experience with MongoDB, Cassandra, or comparable NoSQL platforms. Knowledge of API gateways and service-mesh technologies. Experience with Istio, Linkerd, or comparable service-mesh platforms. Experience with CI/CD and DevOps toolchains. Working knowledge of Jenkins, GitOps, ArgoCD, Terraform, or comparable tools. Strong experience designing logging, monitoring, metrics, and distributed-tracing solutions. Experience with one or more of the following: OpenTelemetry Prometheus Grafana ELK Stack Dynatrace Jaeger Zipkin Proven architecture-governance and technical-leadership experience. Strong client-facing communication and presentation skills. Ability to explain complex technical concepts, options, risks, and trade-offs to both technical and nontechnical audiences. Demonstrated ability to influence technical strategy and guide teams without relying solely on formal authority. Preferred Qualifications Experience leading complex cloud-modernization or monolith-to-microservices programs. Experience supporting multiple enterprise or client engagements. Consulting or systems-integration experience. GCP Professional Cloud Architect certification. Experience establishing enterprise architecture standards or cloud-native reference architectures. Experience designing highly available, high-volume, or mission-critical platforms. Experience conducting architecture assessments and technology-selection initiatives. Experience mentoring architects and senior engineers. Public speaking, technical writing, internal technology leadership, or architecture-community participation. Ideal Candidate The ideal candidate is more than a senior Java developer who has moved into architecture. You have personally owned architecture decisions for complex enterprise platforms and can explain how those decisions improved business, delivery, reliability, or operational outcomes. You remain technically close enough to implementation to guide developers, review designs, evaluate code-level implications, troubleshoot difficult issues, and challenge assumptions. At the same time, you are comfortable presenting to senior client stakeholders and influencing long-term technology strategy. You know how to introduce modern technologies thoughtfully. You evaluate business value, operational complexity, risk, scalability, and long-term maintainability rather than adopting tools simply because they are new. What Success Looks Like Success in this role includes: Building credibility as a trusted technical advisor Improving the quality and consistency of architectural decisions Establishing reusable Java and GCP architecture patterns Helping teams deliver scalable and reliable cloud-native solutions Identifying architecture risks before they become delivery or production issues Strengthening engineering practices across client engagements Contributing technical expertise that expands and deepens client relationships What Makes HTC A Great Place To Build Your Future HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies. At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks. Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
WTW
Java AI Developer
WTW Washington, Washington DC
This job is with WTW, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Description We are seeking a highly skilled Java Developer to join our growing technology team at Individual Marketplace (a LOB inside the HWC segment of WTW). This role involves designing, developing, and maintaining scalable enterprise applications while leveraging AI-native strategies, tools and practices to improve delivery efficiency/speed, code quality, and outcome. The ideal candidate will bring strong expertise in Java-based ecosystems combined with experience in modern engineering practices, DevOps, and AI-powered coding tools (e.g., GitHub Copilot, Claude Code, or similar solutions). You will collaborate with global teams to deliver robust digital solutions that support WTW's business objectives. The Role Design, develop, test, and deploy high-quality, scalable Java applications. Collaborate with architects and cross-functional teams to define technical solutions aligned with business requirements. Leverage AI-assisted development tools and skills to accelerate coding, automate repetitive tasks, and enhance code quality. Participate in code reviews, ensuring adherence to best practices and secure coding standards. Develop and maintain RESTful APIs and microservices. Contribute to CI/CD pipelines and DevOps practices for automated build and deployment processes to Azure Troubleshoot and resolve production issues, ensuring system reliability and performance. Be on call as required to attend incident calls and provide live support. Mentor junior developers and contribute to knowledge sharing within the team. Qualifications The Requirements Bachelor's degree in Computer Science, Information Technology, or related field. 5-8 years of experience in Java development Hands on experience with AI-assisted and AI-native development tools (e.g., GitHub Copilot, OpenAI Codex, Claude Code, etc.). Strong proficiency in: Core Java, Spring Boot, Spring Framework RESTful APIs and Microservices architecture SQL databases Strong understanding of SQL (preferably Oracle SQL) is required. Knowledge on Angular/React is preferred. Knowledge of modern development practices: Agile/Scrum methodologies CI/CD pipelines (Jenkins, Azure DevOps, GitHub Actions) Containerization (Docker, Kubernetes) Familiarity with cloud platforms (Azure preferred). Strong problem-solving skills and ability to work in a collaborative environment. Excellent communication skills. Exposure to security best practices and performance optimization techniques is a plus. Healthcare domain knowledge is preferred Location: Remote Role - Open to anyone residing within the United States Note : Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity. Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only). Compensation The base salary compensation range being offered for this role is $100,000 - $115,000 USD per year. This role is also eligible for an annual short-term incentive bonus. Company Benefits WTW provides a competitive benefit package which includes the following (eligibility requirements apply): Health and Welfare Benefits : Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program) Leave Benefits : Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off (Washington State only) Retirement Benefits : Contributory Pension Plan and Savings Plan (401k). Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records. This position will remain posted for a minimum of three business days from the date posted or until a sufficient/appropriate candidate slate has been identified. EOE, including disability/vets
11/13/2026
Full time
This job is with WTW, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Description We are seeking a highly skilled Java Developer to join our growing technology team at Individual Marketplace (a LOB inside the HWC segment of WTW). This role involves designing, developing, and maintaining scalable enterprise applications while leveraging AI-native strategies, tools and practices to improve delivery efficiency/speed, code quality, and outcome. The ideal candidate will bring strong expertise in Java-based ecosystems combined with experience in modern engineering practices, DevOps, and AI-powered coding tools (e.g., GitHub Copilot, Claude Code, or similar solutions). You will collaborate with global teams to deliver robust digital solutions that support WTW's business objectives. The Role Design, develop, test, and deploy high-quality, scalable Java applications. Collaborate with architects and cross-functional teams to define technical solutions aligned with business requirements. Leverage AI-assisted development tools and skills to accelerate coding, automate repetitive tasks, and enhance code quality. Participate in code reviews, ensuring adherence to best practices and secure coding standards. Develop and maintain RESTful APIs and microservices. Contribute to CI/CD pipelines and DevOps practices for automated build and deployment processes to Azure Troubleshoot and resolve production issues, ensuring system reliability and performance. Be on call as required to attend incident calls and provide live support. Mentor junior developers and contribute to knowledge sharing within the team. Qualifications The Requirements Bachelor's degree in Computer Science, Information Technology, or related field. 5-8 years of experience in Java development Hands on experience with AI-assisted and AI-native development tools (e.g., GitHub Copilot, OpenAI Codex, Claude Code, etc.). Strong proficiency in: Core Java, Spring Boot, Spring Framework RESTful APIs and Microservices architecture SQL databases Strong understanding of SQL (preferably Oracle SQL) is required. Knowledge on Angular/React is preferred. Knowledge of modern development practices: Agile/Scrum methodologies CI/CD pipelines (Jenkins, Azure DevOps, GitHub Actions) Containerization (Docker, Kubernetes) Familiarity with cloud platforms (Azure preferred). Strong problem-solving skills and ability to work in a collaborative environment. Excellent communication skills. Exposure to security best practices and performance optimization techniques is a plus. Healthcare domain knowledge is preferred Location: Remote Role - Open to anyone residing within the United States Note : Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity. Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation (Producer roles only). Compensation The base salary compensation range being offered for this role is $100,000 - $115,000 USD per year. This role is also eligible for an annual short-term incentive bonus. Company Benefits WTW provides a competitive benefit package which includes the following (eligibility requirements apply): Health and Welfare Benefits : Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program) Leave Benefits : Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off (Washington State only) Retirement Benefits : Contributory Pension Plan and Savings Plan (401k). Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records. This position will remain posted for a minimum of three business days from the date posted or until a sufficient/appropriate candidate slate has been identified. EOE, including disability/vets
HP
Agentic AI AI Runtime & Performance Lead
HP Spring, Texas
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime & Performance Lead Description - As the Principal AI Runtime & Performance Lead, this role is responsible for leading AI runtime architecture, performance optimization, and xPU execution strategy. This role is responsible for the design of end-to-end technology solutions necessary to support the business strategy and objectives. The role develops innovative technology solutions that enable strategic initiatives to scale the business efficiently. The role has strong focus on software development and operational excellence using Agile and lean practices to create market differentiated solutions. Houston office in-office requirement: 4 days Responsibilities • Define runtime architecture. • Lead performance optimization efforts. • Drive benchmark methodology. • Develop model execution strategies. • Plays a critical role in building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Leads the building of standards, designs, and automates the deployment of software. • Drives technology strategy and engineering roadmaps around software engineering. • Assists supervisors with project development, including documentation of features, recording of progress, and creation of the testing plan. • Converts business concepts into the next generation of applications and tools, utilizing adaptive agile methodologies to deliver a minimal viable product to the business. • Assists in scheduling, determining manpower requirements, and estimating costs to project completion in order to meet user requirements. • Contributes innovative ideas and may lead large cross-functional teams, exercising independent judgment to solve unique and complex problems impacting the business. • Acts as a functional manager within area of expertise, developing strategy and setting functional policy and direction. • Provides mentorship and guidance to lower-level employees. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong Linux and Windows expertise. • Experience leading cross-functional engineering teams. Preferred Qualifications • Edge AI platforms. • Device telemetry systems. • Firmware integration experience. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
11/13/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime & Performance Lead Description - As the Principal AI Runtime & Performance Lead, this role is responsible for leading AI runtime architecture, performance optimization, and xPU execution strategy. This role is responsible for the design of end-to-end technology solutions necessary to support the business strategy and objectives. The role develops innovative technology solutions that enable strategic initiatives to scale the business efficiently. The role has strong focus on software development and operational excellence using Agile and lean practices to create market differentiated solutions. Houston office in-office requirement: 4 days Responsibilities • Define runtime architecture. • Lead performance optimization efforts. • Drive benchmark methodology. • Develop model execution strategies. • Plays a critical role in building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Leads the building of standards, designs, and automates the deployment of software. • Drives technology strategy and engineering roadmaps around software engineering. • Assists supervisors with project development, including documentation of features, recording of progress, and creation of the testing plan. • Converts business concepts into the next generation of applications and tools, utilizing adaptive agile methodologies to deliver a minimal viable product to the business. • Assists in scheduling, determining manpower requirements, and estimating costs to project completion in order to meet user requirements. • Contributes innovative ideas and may lead large cross-functional teams, exercising independent judgment to solve unique and complex problems impacting the business. • Acts as a functional manager within area of expertise, developing strategy and setting functional policy and direction. • Provides mentorship and guidance to lower-level employees. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong Linux and Windows expertise. • Experience leading cross-functional engineering teams. Preferred Qualifications • Edge AI platforms. • Device telemetry systems. • Firmware integration experience. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
Colt Technology Services
Senior AI Engineer
Colt Technology Services
This job is with Colt Technology Services, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Colt provides network, voice and data centre services to thousands of businesses around the world, allowing them to focus on delivering their business goals instead of the underlying infrastructure. Summary Job title : Senior AI Engineer Reports to : VP of AI Technology and Architecture Job location : Must have ability to be onsite in Boulder, CO office for 2-3 days a week About Colt and the AI Practice Colt Technology Services is a global digital infrastructure company, operating one of the world's largest fiber networks across Europe and Asia. We are building a Boulder-based AI team as the engineering center of our AI Practice. The team is responsible for how AI is adopted, governed, and scaled across Colt. The AI Practice operates across several parallel workstreams, including use case delivery, AI WAN, and private AI. The Boulder team is where we build, test, and validate before we scale. Why we need this role This is a build role. You will take AI use cases from a business problem to something running in production and being used every day: retrieval and search over Colt's own data, agents that carry out multi-step work, and AI built into the systems Colt's teams already rely on. We are looking for a strong software engineer first. If you have spent eight to ten years building and running production systems and even if you have not yet shipped an LLM-based product, we want to hear from. The platform, the tooling, and the model access are already in place, and a staff-level AI engineer on the team will pair with you directly on the AI side of the work. The AI-specific skills you can bring to the table is a plus but is also learnable. The engineering experience and judgement that comes from having owned real systems in production is not, and that is the part we are hiring for. What we do expect is that you have already got hands on with AI, whether at work or as a side project for yourself. You will be working directly with the Colt teams taking requirements from them. The team is small by design, the problems are real, and what you build in your first year sets the pattern for how Colt builds AI. What you will do Build AI Use Cases Design and build AI applications end to end: data access, retrieval, model calls, orchestration, and the interfaces people use Work with large language models through APIs and self-hosted inference, covering prompting, tool use, retrieval, and multi-step agent workflows Build evaluation harnesses that show whether a use case is good enough to ship, and keep owning them after it ships Integrate AI into Colt's existing systems and data, within the constraints of a live enterprise environment Work Directly With the Business Work with the Colt teams, who will be your customers, and who will use what you build, across network operations, service delivery, finance, and others Turn a loosely described business problem into a scoped, buildable design Show working software early and often, and change direction when the first answer turns out to be wrong Be straight with stakeholders about what AI is not the right tool for Take It to Production and Keep It There Move your own work from prototype to production-grade: tested, instrumented, documented, and supportable Monitor accuracy, latency, and cost in production, and act when they drift Work with platform engineers on deployment, and hand over cleanly to production operations Contribute reusable patterns, components, and internal libraries so the next use case is faster than the last What we're looking for Engineering Experience: 8-10+ years building production software. You have owned systems end to end: designed them, shipped them, operated them, and been on the hook when they broke. Languages: Strong in Python, or strong in another language such as Java, Go, C#, or TypeScript and ready to work primarily in Python. Production Systems: APIs and service integration, working with real data at scale, testing, CI/CD, and debugging things that are already live in front of users. Cloud: Comfortable in any major cloud. We build primarily on Google Cloud; equivalent AWS or Azure experience is ok to start. Working Style: Comfortable with ambiguity and with direct contact with non-technical stakeholders. You ask what the problem is before deciding what to build. Hands-On with AI: You have already built something with it under your own steam. A side project, a prototype at work, an internal tool, a serious evaluation you ran, or agentic coding tools you use daily and have opinions about. It does not need to have shipped, been finished, or worked. We want to hear what you tried, what broke, and what you concluded. Helpful, Not Required: Any of this at enterprise scale: production RAG over messy real-world data, agent frameworks, evaluation tooling, Vertex AI, Kubernetes, Terraform. Useful if you have it, and teachable if you do not. HOW YOU WILL RAMP You pair with a staff-level AI engineer from your first week, on a live use case rather than a training exercise The AI platform is already running: model gateway, evaluation tooling, deployment pipelines, and sandbox, development, and production environments We expect you to put something small into real use inside your first 90 days, and to lead a use case end to end within six months WHEN WE TALK Come ready to walk us through something you have built with AI, however small or unfinished. We would rather see a rough prototype you can explain in depth than a polished project you cannot. Expect us to ask where it fell short, what you would do differently, and how you decided whether it was any good. How you evaluated it matters more to us than what you shipped. If you have not used AI tools in your own engineering work, this will be a difficult conversation. That is the one gap we are not set up to close for you. What we offer you: Looking to make a mark? At Colt, you'll make a difference. Because around here, we empower people. We don't tell you what to do. Instead, we employ people we trust, who come together across the globe to create intelligent solutions. Our global teams are full of ambitious, driven people, all working together towards one shared purpose: to put the power of the digital universe in the hands of our customers wherever, whenever and however they want. We give our people the opportunity to inspire and lead teams, and work on projects that connect people, cities, businesses, and ideas. We want you to help us change the world, for the better. Diversity and inclusion Inclusion and valuing diversity of thought and experience are at the heart of our culture here at Colt. From day one, you'll be encouraged to be yourself because we believe that's what helps our people to thrive. We welcome people with diverse backgrounds and experiences, regardless of their gender identity or expression, sexual orientation, race, religion, disability, neurodiversity, age, marital status, pregnancy status, or place of birth. Most recently we have: Signed the UN Women Empowerment Principles which guide our Gender Action Plan Trained 60 (and growing) Colties to be Mental Health First Aiders Please speak with a member of our recruitment team if you require adjustments to our recruitment process to support you. For more information about our Inclusion and Diversity agenda, visit our DEI pages . Benefits Our benefits support you through all parts of life, for both physical and mental health. Flexible working hours and the option to work from home. Extensive induction program with experienced mentors and buddies. Opportunities for further development and educational opportunities. Global Family Leave Policy. Employee Assistance Program. Internal inclusion & diversity employee networks. A global network When you join Colt you become part of our global network. We are proud of our colleagues and the stories and experience they bring - take a look at 'Our People' site including our Empowered Women in Tech.
11/13/2026
Full time
This job is with Colt Technology Services, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Colt provides network, voice and data centre services to thousands of businesses around the world, allowing them to focus on delivering their business goals instead of the underlying infrastructure. Summary Job title : Senior AI Engineer Reports to : VP of AI Technology and Architecture Job location : Must have ability to be onsite in Boulder, CO office for 2-3 days a week About Colt and the AI Practice Colt Technology Services is a global digital infrastructure company, operating one of the world's largest fiber networks across Europe and Asia. We are building a Boulder-based AI team as the engineering center of our AI Practice. The team is responsible for how AI is adopted, governed, and scaled across Colt. The AI Practice operates across several parallel workstreams, including use case delivery, AI WAN, and private AI. The Boulder team is where we build, test, and validate before we scale. Why we need this role This is a build role. You will take AI use cases from a business problem to something running in production and being used every day: retrieval and search over Colt's own data, agents that carry out multi-step work, and AI built into the systems Colt's teams already rely on. We are looking for a strong software engineer first. If you have spent eight to ten years building and running production systems and even if you have not yet shipped an LLM-based product, we want to hear from. The platform, the tooling, and the model access are already in place, and a staff-level AI engineer on the team will pair with you directly on the AI side of the work. The AI-specific skills you can bring to the table is a plus but is also learnable. The engineering experience and judgement that comes from having owned real systems in production is not, and that is the part we are hiring for. What we do expect is that you have already got hands on with AI, whether at work or as a side project for yourself. You will be working directly with the Colt teams taking requirements from them. The team is small by design, the problems are real, and what you build in your first year sets the pattern for how Colt builds AI. What you will do Build AI Use Cases Design and build AI applications end to end: data access, retrieval, model calls, orchestration, and the interfaces people use Work with large language models through APIs and self-hosted inference, covering prompting, tool use, retrieval, and multi-step agent workflows Build evaluation harnesses that show whether a use case is good enough to ship, and keep owning them after it ships Integrate AI into Colt's existing systems and data, within the constraints of a live enterprise environment Work Directly With the Business Work with the Colt teams, who will be your customers, and who will use what you build, across network operations, service delivery, finance, and others Turn a loosely described business problem into a scoped, buildable design Show working software early and often, and change direction when the first answer turns out to be wrong Be straight with stakeholders about what AI is not the right tool for Take It to Production and Keep It There Move your own work from prototype to production-grade: tested, instrumented, documented, and supportable Monitor accuracy, latency, and cost in production, and act when they drift Work with platform engineers on deployment, and hand over cleanly to production operations Contribute reusable patterns, components, and internal libraries so the next use case is faster than the last What we're looking for Engineering Experience: 8-10+ years building production software. You have owned systems end to end: designed them, shipped them, operated them, and been on the hook when they broke. Languages: Strong in Python, or strong in another language such as Java, Go, C#, or TypeScript and ready to work primarily in Python. Production Systems: APIs and service integration, working with real data at scale, testing, CI/CD, and debugging things that are already live in front of users. Cloud: Comfortable in any major cloud. We build primarily on Google Cloud; equivalent AWS or Azure experience is ok to start. Working Style: Comfortable with ambiguity and with direct contact with non-technical stakeholders. You ask what the problem is before deciding what to build. Hands-On with AI: You have already built something with it under your own steam. A side project, a prototype at work, an internal tool, a serious evaluation you ran, or agentic coding tools you use daily and have opinions about. It does not need to have shipped, been finished, or worked. We want to hear what you tried, what broke, and what you concluded. Helpful, Not Required: Any of this at enterprise scale: production RAG over messy real-world data, agent frameworks, evaluation tooling, Vertex AI, Kubernetes, Terraform. Useful if you have it, and teachable if you do not. HOW YOU WILL RAMP You pair with a staff-level AI engineer from your first week, on a live use case rather than a training exercise The AI platform is already running: model gateway, evaluation tooling, deployment pipelines, and sandbox, development, and production environments We expect you to put something small into real use inside your first 90 days, and to lead a use case end to end within six months WHEN WE TALK Come ready to walk us through something you have built with AI, however small or unfinished. We would rather see a rough prototype you can explain in depth than a polished project you cannot. Expect us to ask where it fell short, what you would do differently, and how you decided whether it was any good. How you evaluated it matters more to us than what you shipped. If you have not used AI tools in your own engineering work, this will be a difficult conversation. That is the one gap we are not set up to close for you. What we offer you: Looking to make a mark? At Colt, you'll make a difference. Because around here, we empower people. We don't tell you what to do. Instead, we employ people we trust, who come together across the globe to create intelligent solutions. Our global teams are full of ambitious, driven people, all working together towards one shared purpose: to put the power of the digital universe in the hands of our customers wherever, whenever and however they want. We give our people the opportunity to inspire and lead teams, and work on projects that connect people, cities, businesses, and ideas. We want you to help us change the world, for the better. Diversity and inclusion Inclusion and valuing diversity of thought and experience are at the heart of our culture here at Colt. From day one, you'll be encouraged to be yourself because we believe that's what helps our people to thrive. We welcome people with diverse backgrounds and experiences, regardless of their gender identity or expression, sexual orientation, race, religion, disability, neurodiversity, age, marital status, pregnancy status, or place of birth. Most recently we have: Signed the UN Women Empowerment Principles which guide our Gender Action Plan Trained 60 (and growing) Colties to be Mental Health First Aiders Please speak with a member of our recruitment team if you require adjustments to our recruitment process to support you. For more information about our Inclusion and Diversity agenda, visit our DEI pages . Benefits Our benefits support you through all parts of life, for both physical and mental health. Flexible working hours and the option to work from home. Extensive induction program with experienced mentors and buddies. Opportunities for further development and educational opportunities. Global Family Leave Policy. Employee Assistance Program. Internal inclusion & diversity employee networks. A global network When you join Colt you become part of our global network. We are proud of our colleagues and the stories and experience they bring - take a look at 'Our People' site including our Empowered Women in Tech.
Engineer II, Software Automation
Danaher Irvine, California
This job is with Danaher, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Bring more to life. Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology? At Masimo , one of Danaher's 15+ operating companies, our work saves lives-and we're all united by a shared commitment to innovate for tangible impact. You'll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help turn ideas into impact - innovating at the speed of life. Masimo is a global medical technology company that develops and produces a wide array of industry-leading monitoring technologies, including non-invasive measurements, sensors, patient monitors, and automation and connectivity solutions. Our mission is, Masimo innovations empower clinicians to transform patient care. When you join our team, you'll be part of a culture that's driven by passion, challenging the status quo, and making an impact in the lives of others. Learn about the Danaher Business System which makes everything possible. The Engineer II, Software Automation is responsible for developing, executing, and maintaining scalable test automation frameworks and infrastructure for complex, distributed systems - including microservice-based software platforms, on-prem and cloud deployments, and the in-house and third-party devices they integrate with. This role is a key technical contributor within the Systems Test Engineering organization, developing automation solutions that improve test efficiency, reliability, repeatability, and coverage. The position reports to the Sr Manager, Systems Software Test and is part of the Software Test Engineering department located in Irvine, CA and will be an on-site role. In This Role, You Will Have The Opportunity To: Develop, execute, and maintain scalable automated test frameworks and support infrastructure for instrument and system-level testing. Develop reusable test libraries, device interfaces, protocol libraries, utilities, and common automation components across instrument platforms and downstream system integrations. Contribute to system and product test strategies with an emphasis on automation, repeatability, scalability, and maintainability. Collaborate with development teams during product design to improve system testability, observability, interfaces, communication protocols, and diagnostic capabilities. The Essential Requirements Of The Job Include: B.S. Degree in computer science, computer engineering, software engineering, biomedical engineering, or related technical discipline. 3+ years of experience in software development, test automation, software verification, or a related engineering discipline working with automated testing tools and scripting languages (Python, C#, C++, Java, or similar). Experience with Git, CI/CD systems, and modern software development practices. Familiarity with defect tracking and test management tools. Understanding of Software Development Life Cycle (SDLC) and Agile development methodologies. Strong debugging, problem-solving, communication, and cross-functional collaboration skills. It would be a plus if you also possess previous experience in: Experience within the medical device or other regulated industry. Familiarity with IEC 62304, ISO 13485, FDA Quality System Regulation, or other applicable software quality standards. Familiarity with healthcare interoperability or messaging standards (e.g., HL7, WCTP) or other structured data/protocol formats. Experience with cloud platforms (e.g., AWS, Azure, GCP) and container/orchestration tooling (e.g., Docker, Kubernetes). Masimo, a Danaher operating company, offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it's a health care program or paid time off, our programs contribute to life beyond the job. The annual salary range OR the hourly range for this role is $80,000 - $105,000. This is the range that we in good faith believe is the range of possible compensation for this role at the time of this posting. This range may be modified in the future. This job is also eligible for up to a 10% annual bonus. We offer comprehensive package of benefits including paid time off, medical/dental/vision insurance and 401(k) to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. For more information, visit . Danaher Corporation and all Danaher Companies are committed to equal opportunity regardless of race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity, or other characteristics protected by law. The U.S. EEO posters are available here . For candidates who are based outside of New York City or who are applying for roles outside of New York City, for more information about conditions of any job offer please click here . We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact:1- or .
11/13/2026
Full time
This job is with Danaher, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Bring more to life. Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology? At Masimo , one of Danaher's 15+ operating companies, our work saves lives-and we're all united by a shared commitment to innovate for tangible impact. You'll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help turn ideas into impact - innovating at the speed of life. Masimo is a global medical technology company that develops and produces a wide array of industry-leading monitoring technologies, including non-invasive measurements, sensors, patient monitors, and automation and connectivity solutions. Our mission is, Masimo innovations empower clinicians to transform patient care. When you join our team, you'll be part of a culture that's driven by passion, challenging the status quo, and making an impact in the lives of others. Learn about the Danaher Business System which makes everything possible. The Engineer II, Software Automation is responsible for developing, executing, and maintaining scalable test automation frameworks and infrastructure for complex, distributed systems - including microservice-based software platforms, on-prem and cloud deployments, and the in-house and third-party devices they integrate with. This role is a key technical contributor within the Systems Test Engineering organization, developing automation solutions that improve test efficiency, reliability, repeatability, and coverage. The position reports to the Sr Manager, Systems Software Test and is part of the Software Test Engineering department located in Irvine, CA and will be an on-site role. In This Role, You Will Have The Opportunity To: Develop, execute, and maintain scalable automated test frameworks and support infrastructure for instrument and system-level testing. Develop reusable test libraries, device interfaces, protocol libraries, utilities, and common automation components across instrument platforms and downstream system integrations. Contribute to system and product test strategies with an emphasis on automation, repeatability, scalability, and maintainability. Collaborate with development teams during product design to improve system testability, observability, interfaces, communication protocols, and diagnostic capabilities. The Essential Requirements Of The Job Include: B.S. Degree in computer science, computer engineering, software engineering, biomedical engineering, or related technical discipline. 3+ years of experience in software development, test automation, software verification, or a related engineering discipline working with automated testing tools and scripting languages (Python, C#, C++, Java, or similar). Experience with Git, CI/CD systems, and modern software development practices. Familiarity with defect tracking and test management tools. Understanding of Software Development Life Cycle (SDLC) and Agile development methodologies. Strong debugging, problem-solving, communication, and cross-functional collaboration skills. It would be a plus if you also possess previous experience in: Experience within the medical device or other regulated industry. Familiarity with IEC 62304, ISO 13485, FDA Quality System Regulation, or other applicable software quality standards. Familiarity with healthcare interoperability or messaging standards (e.g., HL7, WCTP) or other structured data/protocol formats. Experience with cloud platforms (e.g., AWS, Azure, GCP) and container/orchestration tooling (e.g., Docker, Kubernetes). Masimo, a Danaher operating company, offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it's a health care program or paid time off, our programs contribute to life beyond the job. The annual salary range OR the hourly range for this role is $80,000 - $105,000. This is the range that we in good faith believe is the range of possible compensation for this role at the time of this posting. This range may be modified in the future. This job is also eligible for up to a 10% annual bonus. We offer comprehensive package of benefits including paid time off, medical/dental/vision insurance and 401(k) to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law. Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. For more information, visit . Danaher Corporation and all Danaher Companies are committed to equal opportunity regardless of race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity, or other characteristics protected by law. The U.S. EEO posters are available here . For candidates who are based outside of New York City or who are applying for roles outside of New York City, for more information about conditions of any job offer please click here . We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact:1- or .
HP
Agentic AI AI Runtime / ML Model Systems Engineer
HP Spring, Texas
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime / ML Model Systems Engineer Description - This role is responsible for developing runtime abstraction layers and intelligent model placement systems across heterogeneous compute resources In this role, you will ensure the technical design, development, installation, and maintenance of state-of-the-art software applications and services for the company. The role plays a crucial role in building technical solutions to help other developers/engineers deliver faster with modern software and application development tools. Houston in-office requirement: 4 days Responsibilities • Build runtime abstraction frameworks. • Implement model placement policies. • Develop xPU routing logic. • Optimize inference execution. • Leads the building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Builds standards, designs, and automates the deployment of software. • Designs and develops solutions that protect and manage software products and data. • Contributes to technology strategy and engineering roadmaps around software engineering; executes strategic software engineering proof of concepts. • Supervises the work of external engineering vendors, analyzing the testing performed by vendors, and provides feedback and expertise to technicians. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 7-10 years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong AI runtime expertise. • Optimize inference execution. Required Qualifications • ONNX, TensorRT, OpenVINO. • NPU/GPU scheduling. • Edge AI deployment. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API ) • Automation • C++ • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $130,700 to $205,200 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - 25% Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
11/13/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime / ML Model Systems Engineer Description - This role is responsible for developing runtime abstraction layers and intelligent model placement systems across heterogeneous compute resources In this role, you will ensure the technical design, development, installation, and maintenance of state-of-the-art software applications and services for the company. The role plays a crucial role in building technical solutions to help other developers/engineers deliver faster with modern software and application development tools. Houston in-office requirement: 4 days Responsibilities • Build runtime abstraction frameworks. • Implement model placement policies. • Develop xPU routing logic. • Optimize inference execution. • Leads the building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Builds standards, designs, and automates the deployment of software. • Designs and develops solutions that protect and manage software products and data. • Contributes to technology strategy and engineering roadmaps around software engineering; executes strategic software engineering proof of concepts. • Supervises the work of external engineering vendors, analyzing the testing performed by vendors, and provides feedback and expertise to technicians. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 7-10 years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong AI runtime expertise. • Optimize inference execution. Required Qualifications • ONNX, TensorRT, OpenVINO. • NPU/GPU scheduling. • Edge AI deployment. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API ) • Automation • C++ • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $130,700 to $205,200 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - 25% Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
Engineer III - API Office
Edward Jones Saint Louis, Missouri
This job posting is anticipated to remain open for 30 days, from 03-Nov-2026. The posting may close early due to the volume of applicants. Join a financial services firm where your contributions are valued. Edward Jones is a Fortune 500 company where people come first. With over 9 million clients and 20,000 financial advisors across the U.S. and Canada, we're proud to be privately-owned, placing the focus on our clients rather than shareholder returns. Behind everything we do is our purpose: We partner for positive impact to improve the lives of our clients and colleagues, and together, better our communities and society. We are an innovative, flexible, and inclusive organization that attracts, develops, and inspires performance excellence and a sense of belonging. People are at the center of our partnership. Edward Jones associates are seen, heard, respected, and supported. This is what we believe makes us the best place to start or build your career. View our Purpose, Inclusion and Citizenship Report . Fortune 500, published June 2024, data as of December 2023. Compensation provided for using, not obtaining, the rating. Team Overview: The mission of the API Office is to empower the Edward Jones Digital community to design, create and maintain impactful API Products by providing API consulting, promoting API lifecycle standards and best practices, and driving execution of the firm's API Strategy to advance overall API maturity. As an API Engineer III in the API Office, you will play a key role in designing and delivering API-first solutions with a strong emphasis on developer experience. You will ensure that solutions are secure, scalable, maintainable, and aligned with enterprise objectives, while collaborating across teams to drive consistency and innovation. What You'll Do: Design, develop, and implement RESTful APIs aligned with Edward Jones standards and industry best practices Partner with Product Owners, Architects, and cross-functional stakeholders to define requirements and deliver solutions from design through deployment Create and maintain clear, comprehensive API documentation for internal and external developers Develop user-facing documentation for API Office services and offerings Implement and enforce security controls, including authentication and authorization to protect systems and information Participate in code reviews and design walkthroughs to ensure code quality, consistency, and maintainability Contribute to on-call support rotations to ensure system reliability and operational excellence Champion API lifecycle management standards and promote an API-first culture across the organization Stay current with emerging technologies, tools, and best practices in API design and integration What Experience You Need 5+ years of experience developing and supporting scalable applications, APIs, HTTP-based integrations, and web services Strong proficiency with Java, Spring Boot, Python, and Node.js Experience building and deploying applications using Docker and Kubernetes Experience working in Microsoft Azure environments Proven ability to design APIs using the OpenAPI Specification (OAS) Solid understanding of API security standards, including OAuth 2.0 and OpenID Connect Experience implementing CI/CD pipelines using tools such as GitHub Actions and related automation technologies What Will Set You Apart Bachelor's degree in computer science, Engineering, or equivalent practical experience Experience with contract testing and API mocking Experience with Rust is a plus Experience with MuleSoft Anypoint Platform for API management Experience collaborating with cross-functional teams to deliver technical solutions Experience working in Agile development environments Experience supporting projects and delivering results in fast-paced, evolving environments "Candidates that live within a commutable distance from our Tempe, AZ and St. Louis, MO home office locations are expected to work in the office four days per week." At Edward Jones, we are building a place where everyone feels like they belong. We're proud of our associates' contributions to the firm and the recognitions we have received. Check out our U.S. awards and accolades: Insights & Information Blog Postings about Edward Jones Check out our Canadian awards and accolades: Insights & Information Blog Postings about Edward Jones Edward Jones does not discriminate on the basis of race, color, gender, religion, national origin, age, disability, sexual orientation, pregnancy, veteran status, genetic information or any other basis prohibited by applicable law. Edward Jones' compensation and benefits package includes medical and prescription drug, dental, vision, voluntary benefits (such as accident, hospital indemnity, and critical illness), short- and long-term disability, basic life, and basic AD&D coverage. Short- and long-term disability, basic life, and basic AD&D coverage are provided at no cost to associates. Edward Jones offers a 401k retirement plan, and tax-advantaged accounts: health savings account, and flexible spending account. Edward Jones observes ten paid holidays and provides 15 days of vacation for new associates beginning on January 1 of each year, as well as sick time, personal days, and a paid day for volunteerism. Associates may be eligible for bonuses and profit sharing. All associates are eligible for the firm's Employee Assistance Program. For more information on the Benefits available to Edward Jones associates, please visit our benefits page .
11/13/2026
Full time
This job posting is anticipated to remain open for 30 days, from 03-Nov-2026. The posting may close early due to the volume of applicants. Join a financial services firm where your contributions are valued. Edward Jones is a Fortune 500 company where people come first. With over 9 million clients and 20,000 financial advisors across the U.S. and Canada, we're proud to be privately-owned, placing the focus on our clients rather than shareholder returns. Behind everything we do is our purpose: We partner for positive impact to improve the lives of our clients and colleagues, and together, better our communities and society. We are an innovative, flexible, and inclusive organization that attracts, develops, and inspires performance excellence and a sense of belonging. People are at the center of our partnership. Edward Jones associates are seen, heard, respected, and supported. This is what we believe makes us the best place to start or build your career. View our Purpose, Inclusion and Citizenship Report . Fortune 500, published June 2024, data as of December 2023. Compensation provided for using, not obtaining, the rating. Team Overview: The mission of the API Office is to empower the Edward Jones Digital community to design, create and maintain impactful API Products by providing API consulting, promoting API lifecycle standards and best practices, and driving execution of the firm's API Strategy to advance overall API maturity. As an API Engineer III in the API Office, you will play a key role in designing and delivering API-first solutions with a strong emphasis on developer experience. You will ensure that solutions are secure, scalable, maintainable, and aligned with enterprise objectives, while collaborating across teams to drive consistency and innovation. What You'll Do: Design, develop, and implement RESTful APIs aligned with Edward Jones standards and industry best practices Partner with Product Owners, Architects, and cross-functional stakeholders to define requirements and deliver solutions from design through deployment Create and maintain clear, comprehensive API documentation for internal and external developers Develop user-facing documentation for API Office services and offerings Implement and enforce security controls, including authentication and authorization to protect systems and information Participate in code reviews and design walkthroughs to ensure code quality, consistency, and maintainability Contribute to on-call support rotations to ensure system reliability and operational excellence Champion API lifecycle management standards and promote an API-first culture across the organization Stay current with emerging technologies, tools, and best practices in API design and integration What Experience You Need 5+ years of experience developing and supporting scalable applications, APIs, HTTP-based integrations, and web services Strong proficiency with Java, Spring Boot, Python, and Node.js Experience building and deploying applications using Docker and Kubernetes Experience working in Microsoft Azure environments Proven ability to design APIs using the OpenAPI Specification (OAS) Solid understanding of API security standards, including OAuth 2.0 and OpenID Connect Experience implementing CI/CD pipelines using tools such as GitHub Actions and related automation technologies What Will Set You Apart Bachelor's degree in computer science, Engineering, or equivalent practical experience Experience with contract testing and API mocking Experience with Rust is a plus Experience with MuleSoft Anypoint Platform for API management Experience collaborating with cross-functional teams to deliver technical solutions Experience working in Agile development environments Experience supporting projects and delivering results in fast-paced, evolving environments "Candidates that live within a commutable distance from our Tempe, AZ and St. Louis, MO home office locations are expected to work in the office four days per week." At Edward Jones, we are building a place where everyone feels like they belong. We're proud of our associates' contributions to the firm and the recognitions we have received. Check out our U.S. awards and accolades: Insights & Information Blog Postings about Edward Jones Check out our Canadian awards and accolades: Insights & Information Blog Postings about Edward Jones Edward Jones does not discriminate on the basis of race, color, gender, religion, national origin, age, disability, sexual orientation, pregnancy, veteran status, genetic information or any other basis prohibited by applicable law. Edward Jones' compensation and benefits package includes medical and prescription drug, dental, vision, voluntary benefits (such as accident, hospital indemnity, and critical illness), short- and long-term disability, basic life, and basic AD&D coverage. Short- and long-term disability, basic life, and basic AD&D coverage are provided at no cost to associates. Edward Jones offers a 401k retirement plan, and tax-advantaged accounts: health savings account, and flexible spending account. Edward Jones observes ten paid holidays and provides 15 days of vacation for new associates beginning on January 1 of each year, as well as sick time, personal days, and a paid day for volunteerism. Associates may be eligible for bonuses and profit sharing. All associates are eligible for the firm's Employee Assistance Program. For more information on the Benefits available to Edward Jones associates, please visit our benefits page .
Engineer III - API Office
Edward Jones Tempe, Arizona
This job posting is anticipated to remain open for 30 days, from 03-Nov-2026. The posting may close early due to the volume of applicants. Join a financial services firm where your contributions are valued. Edward Jones is a Fortune 500 company where people come first. With over 9 million clients and 20,000 financial advisors across the U.S. and Canada, we're proud to be privately-owned, placing the focus on our clients rather than shareholder returns. Behind everything we do is our purpose: We partner for positive impact to improve the lives of our clients and colleagues, and together, better our communities and society. We are an innovative, flexible, and inclusive organization that attracts, develops, and inspires performance excellence and a sense of belonging. People are at the center of our partnership. Edward Jones associates are seen, heard, respected, and supported. This is what we believe makes us the best place to start or build your career. View our Purpose, Inclusion and Citizenship Report . Fortune 500, published June 2024, data as of December 2023. Compensation provided for using, not obtaining, the rating. Team Overview: The mission of the API Office is to empower the Edward Jones Digital community to design, create and maintain impactful API Products by providing API consulting, promoting API lifecycle standards and best practices, and driving execution of the firm's API Strategy to advance overall API maturity. As an API Engineer III in the API Office, you will play a key role in designing and delivering API-first solutions with a strong emphasis on developer experience. You will ensure that solutions are secure, scalable, maintainable, and aligned with enterprise objectives, while collaborating across teams to drive consistency and innovation. What You'll Do: Design, develop, and implement RESTful APIs aligned with Edward Jones standards and industry best practices Partner with Product Owners, Architects, and cross-functional stakeholders to define requirements and deliver solutions from design through deployment Create and maintain clear, comprehensive API documentation for internal and external developers Develop user-facing documentation for API Office services and offerings Implement and enforce security controls, including authentication and authorization to protect systems and information Participate in code reviews and design walkthroughs to ensure code quality, consistency, and maintainability Contribute to on-call support rotations to ensure system reliability and operational excellence Champion API lifecycle management standards and promote an API-first culture across the organization Stay current with emerging technologies, tools, and best practices in API design and integration What Experience You Need 5+ years of experience developing and supporting scalable applications, APIs, HTTP-based integrations, and web services Strong proficiency with Java, Spring Boot, Python, and Node.js Experience building and deploying applications using Docker and Kubernetes Experience working in Microsoft Azure environments Proven ability to design APIs using the OpenAPI Specification (OAS) Solid understanding of API security standards, including OAuth 2.0 and OpenID Connect Experience implementing CI/CD pipelines using tools such as GitHub Actions and related automation technologies What Will Set You Apart Bachelor's degree in computer science, Engineering, or equivalent practical experience Experience with contract testing and API mocking Experience with Rust is a plus Experience with MuleSoft Anypoint Platform for API management Experience collaborating with cross-functional teams to deliver technical solutions Experience working in Agile development environments Experience supporting projects and delivering results in fast-paced, evolving environments "Candidates that live within a commutable distance from our Tempe, AZ and St. Louis, MO home office locations are expected to work in the office four days per week." At Edward Jones, we are building a place where everyone feels like they belong. We're proud of our associates' contributions to the firm and the recognitions we have received. Check out our U.S. awards and accolades: Insights & Information Blog Postings about Edward Jones Check out our Canadian awards and accolades: Insights & Information Blog Postings about Edward Jones Edward Jones does not discriminate on the basis of race, color, gender, religion, national origin, age, disability, sexual orientation, pregnancy, veteran status, genetic information or any other basis prohibited by applicable law. Edward Jones' compensation and benefits package includes medical and prescription drug, dental, vision, voluntary benefits (such as accident, hospital indemnity, and critical illness), short- and long-term disability, basic life, and basic AD&D coverage. Short- and long-term disability, basic life, and basic AD&D coverage are provided at no cost to associates. Edward Jones offers a 401k retirement plan, and tax-advantaged accounts: health savings account, and flexible spending account. Edward Jones observes ten paid holidays and provides 15 days of vacation for new associates beginning on January 1 of each year, as well as sick time, personal days, and a paid day for volunteerism. Associates may be eligible for bonuses and profit sharing. All associates are eligible for the firm's Employee Assistance Program. For more information on the Benefits available to Edward Jones associates, please visit our benefits page .
11/13/2026
Full time
This job posting is anticipated to remain open for 30 days, from 03-Nov-2026. The posting may close early due to the volume of applicants. Join a financial services firm where your contributions are valued. Edward Jones is a Fortune 500 company where people come first. With over 9 million clients and 20,000 financial advisors across the U.S. and Canada, we're proud to be privately-owned, placing the focus on our clients rather than shareholder returns. Behind everything we do is our purpose: We partner for positive impact to improve the lives of our clients and colleagues, and together, better our communities and society. We are an innovative, flexible, and inclusive organization that attracts, develops, and inspires performance excellence and a sense of belonging. People are at the center of our partnership. Edward Jones associates are seen, heard, respected, and supported. This is what we believe makes us the best place to start or build your career. View our Purpose, Inclusion and Citizenship Report . Fortune 500, published June 2024, data as of December 2023. Compensation provided for using, not obtaining, the rating. Team Overview: The mission of the API Office is to empower the Edward Jones Digital community to design, create and maintain impactful API Products by providing API consulting, promoting API lifecycle standards and best practices, and driving execution of the firm's API Strategy to advance overall API maturity. As an API Engineer III in the API Office, you will play a key role in designing and delivering API-first solutions with a strong emphasis on developer experience. You will ensure that solutions are secure, scalable, maintainable, and aligned with enterprise objectives, while collaborating across teams to drive consistency and innovation. What You'll Do: Design, develop, and implement RESTful APIs aligned with Edward Jones standards and industry best practices Partner with Product Owners, Architects, and cross-functional stakeholders to define requirements and deliver solutions from design through deployment Create and maintain clear, comprehensive API documentation for internal and external developers Develop user-facing documentation for API Office services and offerings Implement and enforce security controls, including authentication and authorization to protect systems and information Participate in code reviews and design walkthroughs to ensure code quality, consistency, and maintainability Contribute to on-call support rotations to ensure system reliability and operational excellence Champion API lifecycle management standards and promote an API-first culture across the organization Stay current with emerging technologies, tools, and best practices in API design and integration What Experience You Need 5+ years of experience developing and supporting scalable applications, APIs, HTTP-based integrations, and web services Strong proficiency with Java, Spring Boot, Python, and Node.js Experience building and deploying applications using Docker and Kubernetes Experience working in Microsoft Azure environments Proven ability to design APIs using the OpenAPI Specification (OAS) Solid understanding of API security standards, including OAuth 2.0 and OpenID Connect Experience implementing CI/CD pipelines using tools such as GitHub Actions and related automation technologies What Will Set You Apart Bachelor's degree in computer science, Engineering, or equivalent practical experience Experience with contract testing and API mocking Experience with Rust is a plus Experience with MuleSoft Anypoint Platform for API management Experience collaborating with cross-functional teams to deliver technical solutions Experience working in Agile development environments Experience supporting projects and delivering results in fast-paced, evolving environments "Candidates that live within a commutable distance from our Tempe, AZ and St. Louis, MO home office locations are expected to work in the office four days per week." At Edward Jones, we are building a place where everyone feels like they belong. We're proud of our associates' contributions to the firm and the recognitions we have received. Check out our U.S. awards and accolades: Insights & Information Blog Postings about Edward Jones Check out our Canadian awards and accolades: Insights & Information Blog Postings about Edward Jones Edward Jones does not discriminate on the basis of race, color, gender, religion, national origin, age, disability, sexual orientation, pregnancy, veteran status, genetic information or any other basis prohibited by applicable law. Edward Jones' compensation and benefits package includes medical and prescription drug, dental, vision, voluntary benefits (such as accident, hospital indemnity, and critical illness), short- and long-term disability, basic life, and basic AD&D coverage. Short- and long-term disability, basic life, and basic AD&D coverage are provided at no cost to associates. Edward Jones offers a 401k retirement plan, and tax-advantaged accounts: health savings account, and flexible spending account. Edward Jones observes ten paid holidays and provides 15 days of vacation for new associates beginning on January 1 of each year, as well as sick time, personal days, and a paid day for volunteerism. Associates may be eligible for bonuses and profit sharing. All associates are eligible for the firm's Employee Assistance Program. For more information on the Benefits available to Edward Jones associates, please visit our benefits page .
AI Engineer 4 (Gen AI Platform Services: Agentic AI)
Capital One Mc Lean, Virginia
AI Engineer 4 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 3+ years of experience with Kubernetes Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
AI Engineer 4 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 3+ years of experience with Kubernetes Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX)
Capital One Richmond, Virginia
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field +2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning). +2 years experience leveraging Agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang +2 years Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field +2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning). +2 years experience leveraging Agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang +2 years Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX)
Capital One New York, New York
Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (Gen AI Platform Services: Agentic AI)
Capital One New York, New York
AI Engineer 4 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 3+ years of experience with Kubernetes Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
AI Engineer 4 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 3+ years of experience with Kubernetes Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC)
Capital One Richmond, Virginia
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Machine Learning Experiences (MLX)
Capital One Mc Lean, Virginia
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 4 - Machine Learning Experiences (MLX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ) The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $179,400 - $204,700 for Machine Learning Engineer 4 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5
Capital One New York, New York
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).
11/13/2026
Full time
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).
Senior Manager, Machine Learning Engineer (People Leader)
Capital One Mc Lean, Virginia
Senior Manager, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Senior Manager, Machine Learning Engineer (People Leader) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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