Amazon Development Center U.S., Inc.
Seattle, Washington
In this role, you will own one or more production services and get in on the ground floor of new projects bringing Generative AI to developers worldwide. You will be responsible for revenue, adoption, and the end-to-end product lifecycle of your services. Using your passion for technology and solving customer problems, you will define product strategy, drive execution, and ship offerings that customers love. We are particularly interested in candidates with depth in one or more of the following areas: AI security and safety, responsible AI, or open-source foundation models. As a Senior Technical Product Manager (External Services), you will be the subject matter expert for your area of focus within AWS Compute GenAI services. You will work closely with applied scientists, engineering teams, and go-to-market partners to translate complex technical capabilities into products that are simple for customers to adopt. You will define the roadmap, write the narratives, make the tradeoff calls, and own the results. You will also be part of the broader product leadership community at AWS, contributing to business planning, long-term technical strategy, resource prioritization, and hiring. This community works directly with senior management to set direction and ensure we deliver at the pace our customers expect. A successful candidate will bring: - Proven experience launching technical products and building business around them - Strong business acumen with the ability to own a P&L and drive revenue outcomes - Deep curiosity about generative AI, foundation models, and the developer ecosystem - Comfort operating in ambiguity within a fast-moving organization - The ability to earn trust across engineering, science, and business teams - Desire to have industry-wide impact on how AI is built, deployed, and governed Key job responsibilities Lead Product Definition - Own and drive the customer working backwards strategy, tenets, long-term goals and working backwards documents (press release, FAQ) including customer and market feedback, competitive analysis and business metrics to inform direction. Define Product Vision - Including all aspects to future roadmap, investment, innovation and experimentation. Execution of Product Planning and Development - Including customer goals and business requirements for product release, ensuring implementation is aligned with product goals and requirements, and ownership of product positioning. Lead Product Launch - Own the GTM plan to deliver results that ensure the customer and business goals are met in operational launch plans. Lead Operations - Including monitoring and response to customer feedback, continuous improvement and business growth Lead interaction with Technical Team - Including helping the technical team make tradeoffs based on customer requirements, QA/testing of the product. Business reporting - Track revenue and adoption on a daily basis. Own writing business reports on a weekly and monthly basis and review with leadership. BASIC QUALIFICATIONS - 5+ years of technical product management with internet business experience - 5+ years of working as a Technical Product Manager experience - 3+ years of technical (software development, network development, IT, other related) experience - 7+ years of full product life cycle experience - 5+ years of P&L management and pricing experience - 5+ years of creating written docs for development of new products experience - 5+ years of enterprise security product experience - 5+ years of product management in the cloud computing technology space experience - Bachelor's degree in computer science, engineering, math, finance, or economics - Experience in taking a product from conception & definition phase through engineering design and taking it to market - Experience delivering large-scale SaaS, PaaS or LaaS products where you are responsible for the full product lifecycle, from concept through GTM (go to market) PREFERRED QUALIFICATIONS - Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations - Experience working within teams delivering software products and features using agile methodologies Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 152 900.00 USD annually
09/23/2026
Full time
In this role, you will own one or more production services and get in on the ground floor of new projects bringing Generative AI to developers worldwide. You will be responsible for revenue, adoption, and the end-to-end product lifecycle of your services. Using your passion for technology and solving customer problems, you will define product strategy, drive execution, and ship offerings that customers love. We are particularly interested in candidates with depth in one or more of the following areas: AI security and safety, responsible AI, or open-source foundation models. As a Senior Technical Product Manager (External Services), you will be the subject matter expert for your area of focus within AWS Compute GenAI services. You will work closely with applied scientists, engineering teams, and go-to-market partners to translate complex technical capabilities into products that are simple for customers to adopt. You will define the roadmap, write the narratives, make the tradeoff calls, and own the results. You will also be part of the broader product leadership community at AWS, contributing to business planning, long-term technical strategy, resource prioritization, and hiring. This community works directly with senior management to set direction and ensure we deliver at the pace our customers expect. A successful candidate will bring: - Proven experience launching technical products and building business around them - Strong business acumen with the ability to own a P&L and drive revenue outcomes - Deep curiosity about generative AI, foundation models, and the developer ecosystem - Comfort operating in ambiguity within a fast-moving organization - The ability to earn trust across engineering, science, and business teams - Desire to have industry-wide impact on how AI is built, deployed, and governed Key job responsibilities Lead Product Definition - Own and drive the customer working backwards strategy, tenets, long-term goals and working backwards documents (press release, FAQ) including customer and market feedback, competitive analysis and business metrics to inform direction. Define Product Vision - Including all aspects to future roadmap, investment, innovation and experimentation. Execution of Product Planning and Development - Including customer goals and business requirements for product release, ensuring implementation is aligned with product goals and requirements, and ownership of product positioning. Lead Product Launch - Own the GTM plan to deliver results that ensure the customer and business goals are met in operational launch plans. Lead Operations - Including monitoring and response to customer feedback, continuous improvement and business growth Lead interaction with Technical Team - Including helping the technical team make tradeoffs based on customer requirements, QA/testing of the product. Business reporting - Track revenue and adoption on a daily basis. Own writing business reports on a weekly and monthly basis and review with leadership. BASIC QUALIFICATIONS - 5+ years of technical product management with internet business experience - 5+ years of working as a Technical Product Manager experience - 3+ years of technical (software development, network development, IT, other related) experience - 7+ years of full product life cycle experience - 5+ years of P&L management and pricing experience - 5+ years of creating written docs for development of new products experience - 5+ years of enterprise security product experience - 5+ years of product management in the cloud computing technology space experience - Bachelor's degree in computer science, engineering, math, finance, or economics - Experience in taking a product from conception & definition phase through engineering design and taking it to market - Experience delivering large-scale SaaS, PaaS or LaaS products where you are responsible for the full product lifecycle, from concept through GTM (go to market) PREFERRED QUALIFICATIONS - Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations - Experience working within teams delivering software products and features using agile methodologies Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 152 900.00 USD annually
Benefits: 401(k) Company parties Dental insurance Health insurance Paid time off Benefits/Perks Competitive Compensation Great Work Environment Career Advancement Opportunities Job Summary As a Junior Technical Specialist, you will bring a foundational understanding of technical systems and a desire to learn. You will work under direct supervision in the area of field support of the NAS (National Airspace System) systems, maintenance, and operations. This role will require interfacing with other specialists in hardware, software, and firmware while supporting ASR-9 and RDAS facilities to provide aircraft position and weather information to automation systems for air traffic controllers in terminal airspace. Responsibilities Provide technical assistance and troubleshooting for hardware, software or other technical issues Execute technical procedures related to installation, restoration, and system maintenance Review and comment on system engineering, requirement, and testing documents Support the development of field kits for modifications to the ASR-9 radar Attend design reviews, technical interchange meetings, and any other meetings as requested to support the program and the team Qualifications High School Diploma or GED required and one (1) year of related experience Technical Proficiencies Required Willing to travel on short notice for ASR-9 engineering support/installation Familiarity with Microsoft Office (Excel, Word, etc.) Able to collaborate with a team or work individually on assigned projects The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position. This description is not intended to be an exhaustive list of all responsibilities, duties, and skills required of employees assigned to this job. Management retains the discretion to add or change the duties of the position at any time. Work will be conducted at the William J. Hughes Technical Center. # TO 183 Compensation: $40,000.00 per year EVTKS is a minority veteran-owned small business that provides our customers with the most qualified professionals for their endeavors. Since 2011, EVTKS has been involved in leadership and development. We are proud to lead the way towards a more efficient future with innovative ideas, game-changing technology and polished engineering solutions. We are passionate about connecting people and transforming needs into solutions.
09/23/2026
Full time
Benefits: 401(k) Company parties Dental insurance Health insurance Paid time off Benefits/Perks Competitive Compensation Great Work Environment Career Advancement Opportunities Job Summary As a Junior Technical Specialist, you will bring a foundational understanding of technical systems and a desire to learn. You will work under direct supervision in the area of field support of the NAS (National Airspace System) systems, maintenance, and operations. This role will require interfacing with other specialists in hardware, software, and firmware while supporting ASR-9 and RDAS facilities to provide aircraft position and weather information to automation systems for air traffic controllers in terminal airspace. Responsibilities Provide technical assistance and troubleshooting for hardware, software or other technical issues Execute technical procedures related to installation, restoration, and system maintenance Review and comment on system engineering, requirement, and testing documents Support the development of field kits for modifications to the ASR-9 radar Attend design reviews, technical interchange meetings, and any other meetings as requested to support the program and the team Qualifications High School Diploma or GED required and one (1) year of related experience Technical Proficiencies Required Willing to travel on short notice for ASR-9 engineering support/installation Familiarity with Microsoft Office (Excel, Word, etc.) Able to collaborate with a team or work individually on assigned projects The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position. This description is not intended to be an exhaustive list of all responsibilities, duties, and skills required of employees assigned to this job. Management retains the discretion to add or change the duties of the position at any time. Work will be conducted at the William J. Hughes Technical Center. # TO 183 Compensation: $40,000.00 per year EVTKS is a minority veteran-owned small business that provides our customers with the most qualified professionals for their endeavors. Since 2011, EVTKS has been involved in leadership and development. We are proud to lead the way towards a more efficient future with innovative ideas, game-changing technology and polished engineering solutions. We are passionate about connecting people and transforming needs into solutions.
Leidos has a new and exciting opportunity for a DevOps Engineer in our Intelligence Sector's Cyber & Analytics Business Area (CABA). Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Parental Paid Leave, and much more. Join us and make a difference in National Security! This position is eligible for a $25,000 sign on bonus! Are you seeking a new and challenging position supporting a complex program for the Warfighter, which implements the latest technology? Well, look no further! This is an exciting time to contribute to a mission-critical program with lasting impactful results. Leidos is seeking a highly skilled DevOps Engineer with expertise in Git and extensive experience in platform architecture, automation, and cloud infrastructure. This role requires a deep understanding of Linux and Windows environments, Agile methodologies, and the ability to implement cutting-edge solutions for deployment and system optimization. The ideal candidate is proficient in programming, has a strong background in system administration, and thrives in a collaborative, fast-paced environment. Responsibilities: Support the development lifecycle, including platform design, deployment, and debugging. Build and maintain a release pipeline for fast, secure delivery to production. Automate deployments across environments using scripting languages and toolkits. Configure sites/applications via tools like Puppet and Ansible, and maintain Confluence/Jira software. Assist in designing/maintaining web service infrastructure and deployments. Identify and implement process improvements through automation and streamlining. Required Qualifications: Bachelor's degree or Masters Degree in Engineering (e.g., Computer, Electrical, Mechanical, Aerospace) or Computer Science and 8 years technical experience, with a minimum of 5 years of DevOps experience Fluent with Git and version control best practices, including branching and merging strategies. Strong knowledge of Linux environments (RHEL 6/7/8, RHCSA/RHCE, CentOS) and Windows system administration. Experience integrating Jenkins/Bamboo, Docker, and Kubernetes for automated deployment (preferred). Expertise with caching technologies (e.g., Memcache, Active MQ, Redis, APC), MySQL (Clusters, Replication, Tuning), and Elasticsearch (Kibana a plus). Familiarity with security practices, networking protocols, firewalls, and PCI compliance. Experience with Agile development environments and managing AWS cloud or virtualized servers in PaaS environments. Proficiency in at least one programming language (Ruby, C/C++, Go, Python, or Java) and understanding of object-oriented programming. Clearance Requirement: Top Secret/SCI with Polygraph At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We look forward to learning more about you - apply today! cssrc conmd If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares. Original Posting: June 15, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $107,900.00 - $195,050.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
09/23/2026
Full time
Leidos has a new and exciting opportunity for a DevOps Engineer in our Intelligence Sector's Cyber & Analytics Business Area (CABA). Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Parental Paid Leave, and much more. Join us and make a difference in National Security! This position is eligible for a $25,000 sign on bonus! Are you seeking a new and challenging position supporting a complex program for the Warfighter, which implements the latest technology? Well, look no further! This is an exciting time to contribute to a mission-critical program with lasting impactful results. Leidos is seeking a highly skilled DevOps Engineer with expertise in Git and extensive experience in platform architecture, automation, and cloud infrastructure. This role requires a deep understanding of Linux and Windows environments, Agile methodologies, and the ability to implement cutting-edge solutions for deployment and system optimization. The ideal candidate is proficient in programming, has a strong background in system administration, and thrives in a collaborative, fast-paced environment. Responsibilities: Support the development lifecycle, including platform design, deployment, and debugging. Build and maintain a release pipeline for fast, secure delivery to production. Automate deployments across environments using scripting languages and toolkits. Configure sites/applications via tools like Puppet and Ansible, and maintain Confluence/Jira software. Assist in designing/maintaining web service infrastructure and deployments. Identify and implement process improvements through automation and streamlining. Required Qualifications: Bachelor's degree or Masters Degree in Engineering (e.g., Computer, Electrical, Mechanical, Aerospace) or Computer Science and 8 years technical experience, with a minimum of 5 years of DevOps experience Fluent with Git and version control best practices, including branching and merging strategies. Strong knowledge of Linux environments (RHEL 6/7/8, RHCSA/RHCE, CentOS) and Windows system administration. Experience integrating Jenkins/Bamboo, Docker, and Kubernetes for automated deployment (preferred). Expertise with caching technologies (e.g., Memcache, Active MQ, Redis, APC), MySQL (Clusters, Replication, Tuning), and Elasticsearch (Kibana a plus). Familiarity with security practices, networking protocols, firewalls, and PCI compliance. Experience with Agile development environments and managing AWS cloud or virtualized servers in PaaS environments. Proficiency in at least one programming language (Ruby, C/C++, Go, Python, or Java) and understanding of object-oriented programming. Clearance Requirement: Top Secret/SCI with Polygraph At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We look forward to learning more about you - apply today! cssrc conmd If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares. Original Posting: June 15, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $107,900.00 - $195,050.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role As data and Generative AI applications become increasingly foundational to public sector modernization and national security, safeguarding the infrastructure that powers them is paramount. Databricks is looking for a Sr Technical Solution Engineer to join our Cleared Engineering team in McLean, VA. This team sits at the critical intersection of core infrastructure operations and active platform reliability, ensuring our multi-cloud data enclaves and advanced AI software run flawlessly inside highly secure, air-gapped partitions. In this role, you will move beyond reactive ticketing to tackle complex system and network environment blocks, serving as a primary technical pillar for our secure GovCloud operations. This position offers a unique opportunity to own the operational integrity of high-side platform interactions. You will be responsible for executing sophisticated debugging, deep-dive environment analysis, and running specialized tooling and scripts to unblock internal engineering teams. Operating within a high-consequence compliance framework, you will navigate evolving operational models-including dedicated secure facility operations-while directly engineering out systemic roadblocks. If you are a sharp systems or cloud specialist looking to apply your technical expertise to the world's leading Data and AI platform within the intelligence and defense space, this role offers unmatched technical scope and mission-critical impact. The Impact You'll Have Ensure Platform Reliability: Drive the technical triage, infrastructure visibility, and incident resolution for Databricks' multi-cloud data enclaves and Generative AI software running inside air-gapped environments. Unblock Secure Engineering Pipelines: Serve as the essential secure-zone operational interface, unblocking complex GovCloud system interactions and taking on the analysis and triage burden for internal engineering teams. Execute Advanced Tooling & Scripting: Safely execute and adapt infrastructure scripts, automation tools, and diagnostic workflows natively within secure boundaries, adhering strictly to modern access guidelines. Optimize Environment Patching: Identify and resolve systemic environment blocks, reviewing infrastructure configurations to ensure streamlined, compliant patch deployment pipelines. Maintain Guardrails & Compliance: Navigate and implement evolving operational frameworks within secure facilities (SCIF), ensuring all GovCloud interactions strictly meet rigorous federal security benchmarks. What We're Looking For Minimum Qualifications Active TS/SCI security clearance. 5+ years of experience in Systems Engineering, Cloud Infrastructure, Support Engineering, DevSecOps, or a related technical operational role. High-level proficiency in at least one modern language (Python, Go, Bash, or Java) with the technical aptitude to read, edit, and troubleshoot software and infrastructure code natively. Solid baseline familiarity with Infrastructure-as-Code (IaC) tools such as Terraform or CloudFormation. Hands-on debugging and systems administration experience inside major public cloud boundaries (specifically AWS, Azure, or GCP platforms). Strong foundation in Linux/Unix systems engineering, containers (Docker/Kubernetes orchestration mechanics), and automated patch deployment pipelines. Bachelor's degree in Computer Science, Mathematics, Engineering, or equivalent practical experience. Ability to work out of our McLean, VA secure facility, including flexibility to support 24x7 operational coverage frameworks within a SCIF environment as required. Preferred Qualifications Active Counterintelligence (CI) or Full Scope Polygraph (FSP). Prior experience supporting AWS World Wide Public Sector (WWPS), Oracle Cloud Infrastructure (OCI) Federal Support, or specialized high-side defense integration environments. Demonstrated history of navigating complex federal compliance frameworks, GovCloud boundaries, or air-gapped environment constraints. Strong professional tenure, showing a track record of stability and ownership within complex engineering or defense-intelligence spaces. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $130,200-$178,950 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
09/23/2026
Full time
About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role As data and Generative AI applications become increasingly foundational to public sector modernization and national security, safeguarding the infrastructure that powers them is paramount. Databricks is looking for a Sr Technical Solution Engineer to join our Cleared Engineering team in McLean, VA. This team sits at the critical intersection of core infrastructure operations and active platform reliability, ensuring our multi-cloud data enclaves and advanced AI software run flawlessly inside highly secure, air-gapped partitions. In this role, you will move beyond reactive ticketing to tackle complex system and network environment blocks, serving as a primary technical pillar for our secure GovCloud operations. This position offers a unique opportunity to own the operational integrity of high-side platform interactions. You will be responsible for executing sophisticated debugging, deep-dive environment analysis, and running specialized tooling and scripts to unblock internal engineering teams. Operating within a high-consequence compliance framework, you will navigate evolving operational models-including dedicated secure facility operations-while directly engineering out systemic roadblocks. If you are a sharp systems or cloud specialist looking to apply your technical expertise to the world's leading Data and AI platform within the intelligence and defense space, this role offers unmatched technical scope and mission-critical impact. The Impact You'll Have Ensure Platform Reliability: Drive the technical triage, infrastructure visibility, and incident resolution for Databricks' multi-cloud data enclaves and Generative AI software running inside air-gapped environments. Unblock Secure Engineering Pipelines: Serve as the essential secure-zone operational interface, unblocking complex GovCloud system interactions and taking on the analysis and triage burden for internal engineering teams. Execute Advanced Tooling & Scripting: Safely execute and adapt infrastructure scripts, automation tools, and diagnostic workflows natively within secure boundaries, adhering strictly to modern access guidelines. Optimize Environment Patching: Identify and resolve systemic environment blocks, reviewing infrastructure configurations to ensure streamlined, compliant patch deployment pipelines. Maintain Guardrails & Compliance: Navigate and implement evolving operational frameworks within secure facilities (SCIF), ensuring all GovCloud interactions strictly meet rigorous federal security benchmarks. What We're Looking For Minimum Qualifications Active TS/SCI security clearance. 5+ years of experience in Systems Engineering, Cloud Infrastructure, Support Engineering, DevSecOps, or a related technical operational role. High-level proficiency in at least one modern language (Python, Go, Bash, or Java) with the technical aptitude to read, edit, and troubleshoot software and infrastructure code natively. Solid baseline familiarity with Infrastructure-as-Code (IaC) tools such as Terraform or CloudFormation. Hands-on debugging and systems administration experience inside major public cloud boundaries (specifically AWS, Azure, or GCP platforms). Strong foundation in Linux/Unix systems engineering, containers (Docker/Kubernetes orchestration mechanics), and automated patch deployment pipelines. Bachelor's degree in Computer Science, Mathematics, Engineering, or equivalent practical experience. Ability to work out of our McLean, VA secure facility, including flexibility to support 24x7 operational coverage frameworks within a SCIF environment as required. Preferred Qualifications Active Counterintelligence (CI) or Full Scope Polygraph (FSP). Prior experience supporting AWS World Wide Public Sector (WWPS), Oracle Cloud Infrastructure (OCI) Federal Support, or specialized high-side defense integration environments. Demonstrated history of navigating complex federal compliance frameworks, GovCloud boundaries, or air-gapped environment constraints. Strong professional tenure, showing a track record of stability and ownership within complex engineering or defense-intelligence spaces. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $130,200-$178,950 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
About Nscale Nscale is taking on the hyperscalers by building a vertically integrated GenAI cloud platform. We own the data centres, software, and applications that power today's AI stack using sustainable technology solutions. We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you'll build trust through openness and transparency, where everyone is inspired to do their best work. Collaboration is key, and we work together swiftly and respectfully, embracing adaptability and resilience in all we do. About the role Technical Product Managers at Nscale own the definition, delivery, and ongoing evolution of a slice of the Nscale platform. You partner closely with engineering, design, research, and go-to-market teams to translate customer problems and operational realities into shippable product outcomes. As a Senior Technical Product Manager for Fleet Operations, you own the product strategy for the day 0-2+ operational software that runs our global GPU fleet - the systems that bring capacity online, keep it healthy, and restore it fast when things go wrong. You partner daily with Fleet Software engineering teams, SRE, and Support to turn operational pain into durable product: provisioning and bringup (day 0), testing and deployment (day 1), and the full lifecycle of monitoring, incident response, repair, RMA, firmware, and decommissioning (day 2+). You operate at team scope, owning a major product area and driving multi-quarter initiatives that directly move fleet availability, utilisation, and time-to-recover. Senior Technical Product Manager, Fleet Operations 1 What you'll be doing Own the strategy and roadmap for a significant Fleet Operations product area - e.g. provisioning and bring-up, fleet health and telemetry, incident and repair workflows, firmware and lifecycle management, or capacity and inventory. Lead multi-sprint, cross-functional initiatives from problem framing through rollout across live GPU clusters, working hand-in-hand with Fleet Software, SRE, data centre operations, and Support. Turn operational ambiguity into product: shadow on-call rotations, ride along with support and repair workflows, and translate recurring toil into tooling, automation, and platform capabilities. Define the metrics that matter for a GPU fleet - availability, utilisation, MTTR, time-to-bring-up, hardware failure rates, support ticket deflection - and drive the roadmap against them. Partner with engineering on architecture and trade-offs for systems that span bare metal, orchestration, observability, and control planes. Drive incident reviews and postmortems into product commitments; close the loop so the same class of issue doesn't recur. Mentor junior product managers and raise the quality bar for PRDs, reviews, and product decisions across the team. Represent Fleet Operations in planning, reviews, and leadership updates. What you need 5-8 years of product management experience in software or technology, with a track record of owning significant product areas in infrastructure, platform, or operations-facing products. Strong technical fluency in large-scale systems: you can lead discussions with engineering on architecture, trade-offs, and feasibility across provisioning, orchestration, observability, and control-plane design Experience building products for operators - SREs, NOC/support teams, data centre technicians, or similar - and a genuine appetite for understanding their workflows. Demonstrated ability to move from an ambiguous operational problem space to shipped product outcomes that measurably improve reliability, efficiency, or time-to-recover. Experience mentoring or informally leading peers. Excellent written and verbal communication; you can make complex product decisions legible to engineers, operators, and executives alike. Experience with data centre networking technologies, including high-performance GPU interconnects such as InfiniBand and RoCE (RDMA over Converged Ethernet), and an understanding of how backend (east-west/compute) and frontend (north-south/storage and management) network fabrics are designed and operated at scale. Familiarity with WAN, edge, and global backbone architectures - including how multi-site connectivity, peering, and traffic engineering support a globally distributed GPU fleet. Experience partnering with network engineering teams on fabric health, congestion monitoring, and link-level failure workflows, ideally in environments where network performance directly impacts training or inference workloads. Nice to haves Degree in computer science, engineering, or a related field, or prior experience as an engineer or SRE. Hands-on background in cloud infrastructure, bare-metal provisioning, fleet or hardware lifecycle management, observability/monitoring platforms, or incident management tooling. Experience with bare-metal provisioning systems such as OpenStack Ironic (or equivalents like MAAS, Tinkerbell, or in-house provisioning stacks). Experience with DCIM tools such as NetBox (or equivalents like Device42 or Nautobot) for inventory, cabling, and rack/asset management. Experience with ITSM and ticketing platforms such as Jira Service Management (or equivalents like ServiceNow, Zendesk, or Freshservice) for support, incident, and RMA workflows. Experience with observability and monitoring platforms such as Grafana, Prometheus, Datadog, or equivalents - ideally including defining SLOs, dashboards, and alerting for large fleets. Familiarity with GPU or accelerated compute environments, data centre operations, or hyperscaler-style fleet management. Experience operating in high-growth or early-stage environments where the product is being built alongside the fleet itself Join Nscale as we build a world-class AI cloud platform. If you're excited about owning the software that keeps a global GPU fleet running - and raising the bar for the team around you - we'd love to hear from you! At Nscale, we are committed to fostering an inclusive, diverse, and equitable workplace. We believe that a variety of perspectives enriches our work environment, and we encourage applications from candidates of all backgrounds, experiences, and abilities. We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds. If there's anything we can do to accommodate your specific situation, please let us know. The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role. The range below reflects the base salary for the position. Actual compensation may vary based on job-related factors such as skill set, experience, education, and location. In addition to base salary, this role may be eligible for bonus, equity, and/or commission programs. Nscale may offer a competitive benefits package including medical, dental, vision, flexible paid time off, parental leave, and retirement plan participation. Salary Range $200,000-$280,000 USD For information on how Nscale handles candidate personal data, please see our Employee & Candidate Privacy Notice: Here. Nscale does not accept unsolicited candidate submissions from recruitment agencies.
09/23/2026
Full time
About Nscale Nscale is taking on the hyperscalers by building a vertically integrated GenAI cloud platform. We own the data centres, software, and applications that power today's AI stack using sustainable technology solutions. We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you'll build trust through openness and transparency, where everyone is inspired to do their best work. Collaboration is key, and we work together swiftly and respectfully, embracing adaptability and resilience in all we do. About the role Technical Product Managers at Nscale own the definition, delivery, and ongoing evolution of a slice of the Nscale platform. You partner closely with engineering, design, research, and go-to-market teams to translate customer problems and operational realities into shippable product outcomes. As a Senior Technical Product Manager for Fleet Operations, you own the product strategy for the day 0-2+ operational software that runs our global GPU fleet - the systems that bring capacity online, keep it healthy, and restore it fast when things go wrong. You partner daily with Fleet Software engineering teams, SRE, and Support to turn operational pain into durable product: provisioning and bringup (day 0), testing and deployment (day 1), and the full lifecycle of monitoring, incident response, repair, RMA, firmware, and decommissioning (day 2+). You operate at team scope, owning a major product area and driving multi-quarter initiatives that directly move fleet availability, utilisation, and time-to-recover. Senior Technical Product Manager, Fleet Operations 1 What you'll be doing Own the strategy and roadmap for a significant Fleet Operations product area - e.g. provisioning and bring-up, fleet health and telemetry, incident and repair workflows, firmware and lifecycle management, or capacity and inventory. Lead multi-sprint, cross-functional initiatives from problem framing through rollout across live GPU clusters, working hand-in-hand with Fleet Software, SRE, data centre operations, and Support. Turn operational ambiguity into product: shadow on-call rotations, ride along with support and repair workflows, and translate recurring toil into tooling, automation, and platform capabilities. Define the metrics that matter for a GPU fleet - availability, utilisation, MTTR, time-to-bring-up, hardware failure rates, support ticket deflection - and drive the roadmap against them. Partner with engineering on architecture and trade-offs for systems that span bare metal, orchestration, observability, and control planes. Drive incident reviews and postmortems into product commitments; close the loop so the same class of issue doesn't recur. Mentor junior product managers and raise the quality bar for PRDs, reviews, and product decisions across the team. Represent Fleet Operations in planning, reviews, and leadership updates. What you need 5-8 years of product management experience in software or technology, with a track record of owning significant product areas in infrastructure, platform, or operations-facing products. Strong technical fluency in large-scale systems: you can lead discussions with engineering on architecture, trade-offs, and feasibility across provisioning, orchestration, observability, and control-plane design Experience building products for operators - SREs, NOC/support teams, data centre technicians, or similar - and a genuine appetite for understanding their workflows. Demonstrated ability to move from an ambiguous operational problem space to shipped product outcomes that measurably improve reliability, efficiency, or time-to-recover. Experience mentoring or informally leading peers. Excellent written and verbal communication; you can make complex product decisions legible to engineers, operators, and executives alike. Experience with data centre networking technologies, including high-performance GPU interconnects such as InfiniBand and RoCE (RDMA over Converged Ethernet), and an understanding of how backend (east-west/compute) and frontend (north-south/storage and management) network fabrics are designed and operated at scale. Familiarity with WAN, edge, and global backbone architectures - including how multi-site connectivity, peering, and traffic engineering support a globally distributed GPU fleet. Experience partnering with network engineering teams on fabric health, congestion monitoring, and link-level failure workflows, ideally in environments where network performance directly impacts training or inference workloads. Nice to haves Degree in computer science, engineering, or a related field, or prior experience as an engineer or SRE. Hands-on background in cloud infrastructure, bare-metal provisioning, fleet or hardware lifecycle management, observability/monitoring platforms, or incident management tooling. Experience with bare-metal provisioning systems such as OpenStack Ironic (or equivalents like MAAS, Tinkerbell, or in-house provisioning stacks). Experience with DCIM tools such as NetBox (or equivalents like Device42 or Nautobot) for inventory, cabling, and rack/asset management. Experience with ITSM and ticketing platforms such as Jira Service Management (or equivalents like ServiceNow, Zendesk, or Freshservice) for support, incident, and RMA workflows. Experience with observability and monitoring platforms such as Grafana, Prometheus, Datadog, or equivalents - ideally including defining SLOs, dashboards, and alerting for large fleets. Familiarity with GPU or accelerated compute environments, data centre operations, or hyperscaler-style fleet management. Experience operating in high-growth or early-stage environments where the product is being built alongside the fleet itself Join Nscale as we build a world-class AI cloud platform. If you're excited about owning the software that keeps a global GPU fleet running - and raising the bar for the team around you - we'd love to hear from you! At Nscale, we are committed to fostering an inclusive, diverse, and equitable workplace. We believe that a variety of perspectives enriches our work environment, and we encourage applications from candidates of all backgrounds, experiences, and abilities. We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds. If there's anything we can do to accommodate your specific situation, please let us know. The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role. The range below reflects the base salary for the position. Actual compensation may vary based on job-related factors such as skill set, experience, education, and location. In addition to base salary, this role may be eligible for bonus, equity, and/or commission programs. Nscale may offer a competitive benefits package including medical, dental, vision, flexible paid time off, parental leave, and retirement plan participation. Salary Range $200,000-$280,000 USD For information on how Nscale handles candidate personal data, please see our Employee & Candidate Privacy Notice: Here. Nscale does not accept unsolicited candidate submissions from recruitment agencies.
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
09/23/2026
Full time
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
09/23/2026
Full time
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
09/23/2026
Full time
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
09/23/2026
Full time
Become a part of our caring community Step into a high impact role where you'll be at the forefront of keeping critical applications running smoothly and reliably. You will lead the response to complex production incidents, bringing together experts across teams to rapidly restore service and drive lasting improvements. Partnering closely with engineering, you'll help deliver innovative solutions and ensure new releases reach production with minimal disruption. If you thrive in a fast-paced environment and enjoy solving challenging problems, this is an opportunity to make a visible impact every day. The Senior Technology Leadership Professional maintains, integrates, and analyzes software applications within the organization. The Senior Technology Leadership Professional work assignments involve moderately complex to complex issues on where the analysis of situations or data requires an in-depth evaluation of solutions built on leading-edge technology like AI and Gen AI. This position emphasizes providing technical support for production environments, diagnosing, and resolving issues to ensure system stability. It requires a deep understanding of the system architecture and the ability to troubleshoot complex problems promptly. The Senior Technology Leadership Professional collaborates with application teams, quality assurance, configuration, deployment , and support to ensure smooth, stable and timely implementation of new software and updates to installed applications via operational excellence. Ensures proper controls are established and maintained over test and production systems and software source code. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments. Use your skills to make an impact Required Qualifications Bachelor's degree or equivalent work experience. Experience with Databases, ETL and other data transformation tools, provides our partners assistance with Database Design, Database modeling, Database Replication and Data warehousing supporting big data technologies like Synapse, Hyperscale, Kafka Experience with Azure Databricks, ADF, PySpark, Google Cloud Platform (GCP), & Azure Kubernetes Experience with monitoring Tools - SPLUNK and Dynatrace 2 or more years of project leadership experience. Deep understanding of distributed systems, cloud-based architectures, and infrastructure as code principles. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Ability to manage multiple tasks and deadlines with attention to detail. Ability to communicate effectively and deliver presentations to senior leaders. Advanced experience leading special projects and producing metrics, measurements, and trend reports. Must be passionate about contributing to an organization focused on continuously improving consumer experiences. Preferred Qualifications Azure Certifications Possess a solid understanding of operations, technology, communications, and processes Experience with technology solutions assessments and/or strategy planning oversight Experience with DevOps Cloud platform certification (Azure, GCP) Work at Home Requirements: To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain roles, the minimum recommended internet speed required by Humana may not be sufficient for business needs. Humana reserves the right to require associates to upgrade their internet service if necessary. Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$106,900 - $147,000 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health - delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at and at Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
Date Posted: 2026-08-17 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 805 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. The Software organization develops software applications, including integration and test on missiles, launchers, radars, naval systems, fire control and other complex systems. Our precision software and firmware integrate operating systems, device drivers, networking, and control software to bring together sensor, guidance, and flight control processing features to complete the mission. The Software org is made up of several Centers located across the country, responsible for all aspects of the software development lifecycle. Our 4000+ software engineers design, develop, and build innovative solutions for our customers. Join our fast-paced agile teams on the leading edge of technology. As part of the Software Engineering Directorate's (SWE) Effectors Center (EC) team, you will be an integral part of helping Raytheon further our vision to be the global leader in core and next-generation weapon and security solutions. By any measure, Raytheon is an exciting and rewarding place to work. We pride ourselves on developing mission-driven, world-class talent. The result is a workforce that takes pride in the company and consistently delivers superior solutions. Our Senior Principal Embedded Real-Time Software Developer/Integrator is a technical position that works in an Integrated Product Team (IPT) environment to architect, design, implement, test, debug, and deploy Software for Firmware (FPGA) and Hardware solutions that meet current and next generation autonomous avionics systems' needs. Working with a cross-discipline team, the candidate must have experience developing, testing, and integrating software for edge or embedded devices and/or subsystems (like telecom, medical, IoT, automotive, or robotics) where hardware operation, time critical function, functional reliability, mission assurance, and safety might be major concerns. The successful candidate will work with Product Owners, Chief Engineers, Management and other IPT members using Lean and/or Agile practices to ensure that embedded software is designed and developed to reliably operate toward the intended functions. This position is within the Effectors Center of the Software organization, and is an onsite role located in Tucson, AZ. What You Will Do Architecting, designing, implementing, testing, and debugging integrated embedded real-time software within heterogenous systems composed of firmware and hardware Working within a cross-discipline team to define, refine, and improve product concept, implementation, testability, and guaranteed, measurable quality Teaching, coaching, and mentoring less experienced staff Contributing to proposals as well as preliminary and critical design reviews Ability to obtain program access What You Will Learn Working across a product line in collaboration with other teams Qualifications You Must Have Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and a minimum of 10 years of prior relevant experience. Experience including at least two of the following: Embedded C++ Software, Embedded Software Security, Software Architecture Design and Implementation. Experience using embedded Real Time Operating Systems (RTOS) (e.g., Green Hills, Integrity, Wind River VxWorks, Linux, etc.). Experience developing complex systems involving the integration of hardware, firmware, and software. Active and transferable Secret U.S. government issued security clearance is required prior to start date with the ability to obtain program access after start. Qualifications We Prefer Familiarity with rate monotonic theory, practice, and limitations Familiarity with layered architectural principles, and their limitations Familiarity with reading electrical schematics and relating it to software function Familiarity with reading firmware source like VHDL or Verilog Familiarity with assembly language in at least one processor/controller family Experience using lab instruments like power-supplies, digital multi-meters, oscilloscopes, and logic analyzers Experience with developing device drivers for bare-metal and/or OS applications Experience leading engineering teams in delivering systems (of various size) involving the integration of hardware and software. What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Safety, Trust, Respect, Accountability, Collaboration, and Innovation. Relocation Offered Based On Eligibility Learn More & Apply Now! Please consider the following role type definition as you apply for this role: Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. Clearance Information: This position requires a security clearance. DCSA Consolidated Adjudication Services (DCSA CAS), an agency of the Department of Defense, handles and adjudicates the security clearance process. More information about Security Clearances can be found on the US Department of State government website here: Location Information: This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links "Raytheon In Tucson": ,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 132,400 USD - 251,600 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. . click apply for full job details
09/23/2026
Full time
Date Posted: 2026-08-17 Country: United States of America Location: US-AZ-TUCSON- E Hermans Rd BLDG 805 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: Secret - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. The Software organization develops software applications, including integration and test on missiles, launchers, radars, naval systems, fire control and other complex systems. Our precision software and firmware integrate operating systems, device drivers, networking, and control software to bring together sensor, guidance, and flight control processing features to complete the mission. The Software org is made up of several Centers located across the country, responsible for all aspects of the software development lifecycle. Our 4000+ software engineers design, develop, and build innovative solutions for our customers. Join our fast-paced agile teams on the leading edge of technology. As part of the Software Engineering Directorate's (SWE) Effectors Center (EC) team, you will be an integral part of helping Raytheon further our vision to be the global leader in core and next-generation weapon and security solutions. By any measure, Raytheon is an exciting and rewarding place to work. We pride ourselves on developing mission-driven, world-class talent. The result is a workforce that takes pride in the company and consistently delivers superior solutions. Our Senior Principal Embedded Real-Time Software Developer/Integrator is a technical position that works in an Integrated Product Team (IPT) environment to architect, design, implement, test, debug, and deploy Software for Firmware (FPGA) and Hardware solutions that meet current and next generation autonomous avionics systems' needs. Working with a cross-discipline team, the candidate must have experience developing, testing, and integrating software for edge or embedded devices and/or subsystems (like telecom, medical, IoT, automotive, or robotics) where hardware operation, time critical function, functional reliability, mission assurance, and safety might be major concerns. The successful candidate will work with Product Owners, Chief Engineers, Management and other IPT members using Lean and/or Agile practices to ensure that embedded software is designed and developed to reliably operate toward the intended functions. This position is within the Effectors Center of the Software organization, and is an onsite role located in Tucson, AZ. What You Will Do Architecting, designing, implementing, testing, and debugging integrated embedded real-time software within heterogenous systems composed of firmware and hardware Working within a cross-discipline team to define, refine, and improve product concept, implementation, testability, and guaranteed, measurable quality Teaching, coaching, and mentoring less experienced staff Contributing to proposals as well as preliminary and critical design reviews Ability to obtain program access What You Will Learn Working across a product line in collaboration with other teams Qualifications You Must Have Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and a minimum of 10 years of prior relevant experience. Experience including at least two of the following: Embedded C++ Software, Embedded Software Security, Software Architecture Design and Implementation. Experience using embedded Real Time Operating Systems (RTOS) (e.g., Green Hills, Integrity, Wind River VxWorks, Linux, etc.). Experience developing complex systems involving the integration of hardware, firmware, and software. Active and transferable Secret U.S. government issued security clearance is required prior to start date with the ability to obtain program access after start. Qualifications We Prefer Familiarity with rate monotonic theory, practice, and limitations Familiarity with layered architectural principles, and their limitations Familiarity with reading electrical schematics and relating it to software function Familiarity with reading firmware source like VHDL or Verilog Familiarity with assembly language in at least one processor/controller family Experience using lab instruments like power-supplies, digital multi-meters, oscilloscopes, and logic analyzers Experience with developing device drivers for bare-metal and/or OS applications Experience leading engineering teams in delivering systems (of various size) involving the integration of hardware and software. What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Safety, Trust, Respect, Accountability, Collaboration, and Innovation. Relocation Offered Based On Eligibility Learn More & Apply Now! Please consider the following role type definition as you apply for this role: Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. Clearance Information: This position requires a security clearance. DCSA Consolidated Adjudication Services (DCSA CAS), an agency of the Department of Defense, handles and adjudicates the security clearance process. More information about Security Clearances can be found on the US Department of State government website here: Location Information: This position is onsite at our campus in beautiful Tucson, AZ. Tucson has a friendly, caring, and laid-back atmosphere, combined with the innovation and energy of a metropolitan region, and recognized as one of America's 10 Best Small Cities. Surrounded by beautiful mountains, colorful Sonoran Desert landscape and majestic saguaro cacti, Tucson is blessed with some of nature's best work. Tucson is known for its bright blue skies, and with more than 310 sunny days per year, Tucson's fantastic weather lets residents enjoy the outdoors year-round. Virtual Fly Over City of Tucson & Community, YouTube Video Links "Raytheon In Tucson": ,-az-location "Tucson is Awesome": "Winter in Tucson": As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 132,400 USD - 251,600 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. . click apply for full job details
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/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. Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 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).
09/23/2026
Full time
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/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. Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, 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).
09/22/2026
Full time
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, 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).
09/22/2026
Full time
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, 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).
09/22/2026
Full time
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, 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).
09/22/2026
Full time
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) 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. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. 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. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, 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).
L3Harris is dedicated to recruiting and developing high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers' mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do. L3Harris is the Trusted Disruptor in defense tech. With customers' mission-critical needs always in mind, our employees deliver end-to-end technology solutions connecting the space, air, land, sea and cyber domains in the interest of national security. Job Title: Senior Specialist, Integration & Test Engineer Job Code: 42447 Job Location: Melbourne, Florida Job Schedule: 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked, and have every other Friday off Job Description: L3Harris Intelligence & Cyber Sector, within the Space and Mission Systems Segment, is seeking an experienced System Software Integration and Test Engineer to support complex cyber-resilient, cloud-based solutions across the full product lifecycle. The selected candidate will lead and support system integration and test activities, including requirements analysis for testability, test architecture development, integration planning, verification execution, anomaly resolution, and production support, while developing and executing test plans, procedures, and integration flows for subsystems, lower-level assemblies, and end-to-end First Article testing. Additional responsibilities include coordinating integration activities across test beds, hardware/software-in-the-loop environments, and software simulators developed internally and by subcontractors. The engineer will define and implement verification strategies, support requirements traceability and compliance, evaluate subsystem- and system-level performance, and collaborate cross-functionally with systems engineering, software engineering, quality, operations, and external partners to resolve technical issues and ensure successful execution of system-level integration and verification objectives. The ideal candidate will have experience with complex system integration, aerospace or spacecraft test environments, and structured verification and validation processes. Essential Functions: Oversee the integration and testing of lower-level software components through subsystem and application-level verification. Develop and maintain test documentation, including Test Requirements Documents, Test Design Documents (TDDs), Test Plans, and test procedures. Support and direct personnel in the execution of secure software solutions, including vulnerability scanning, secure interface verification, continuous update testing, and compliance documentation validation prior to release. Develop and execute functional, performance, integration, and qualification test procedures, and document results to verify compliance with program requirements. Support test environment setup, script development, test procedure development, implementation, checkout of software test platforms, and evaluation of analysis tools, as required. Identify, document, track, and assist in resolving software integration and test issues through closure. Analyze test results, identify anomalies, and collaborate with development teams to determine root cause and support corrective actions. Represent Software Integration and Test in major technical reviews, including SRR, SDR, PDR, CDR, and TRR. Partner with cross-functional teams, including Systems Engineering, Project Engineering, Cybersecurity, and Software Engineering, during requirements analysis and verification planning, including development and maintenance of the Requirements Verification Traceability Matrix (RVTM). Support secure software deployment activities and ensure verification of software baselines, interfaces, and configuration changes. Work extended and weekend hours, as needed, during critical program integration and test phases. Be available to travel up to 10%, as required. Qualifications: Bachelor's Degree and minimum 6 years of prior relevant experience. Graduate Degree and a minimum of 4 years of prior related experience. In lieu of a degree, minimum of 10 years of prior related experience. Active TS/SCI clearance. Preferred Additional Skills: 2+ years of network administration experience including configuration of firewalls, VPNs, zero-trust models in support of software-defined cloud networking. 2+ years with CRA Software integration, testing, and troubleshooting. Experience working on defense systems, including space payloads, spacecraft buses, ground systems, and environmental testing. Experience with the five pillars of cyber resilience; prepare/identify, protect, detect, respond, and recover. Experience with hardware and software requirements testability, requirements definition, block diagrams, interconnect diagrams, and hardware/software integration. Experience using DOORS and/or MBSE tools such as Cameo and Magic Draw are a plus. Experience with automation and scripting languages such as Java, Python, and Perl. Experience with Jira, Bitbucket, Confluence, and source control tools. Hands-on experience with RF test and measurement equipment, including modems, emulators, spectrum analyzers, network analyzers, logic analyzers, signal generators, oscilloscopes, and power sensors, in support of integration, verification, and system performance evaluation. L3Harris Technologies is proud to be an Equal Opportunity Employer. L3Harris is committed to treating all employees and applicants for employment with respect and dignity and maintaining a workplace that is free from unlawful discrimination. All applicants will be considered for employment without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender (including pregnancy, childbirth, breastfeeding or other related medical conditions), gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, characteristic or membership in any other group protected by federal, state or local laws. L3Harris maintains a drug-free workplace and performs pre-employment substance abuse testing and background checks, where permitted by law. Please be aware many of our positions require the ability to obtain a security clearance. Security clearances may only be granted to U.S. citizens. In addition, applicants who accept a conditional offer of employment may be subject to government security investigation(s) and must meet eligibility requirements for access to classified information. By submitting your resume for this position, you understand and agree that L3Harris Technologies may share your resume, as well as any other related personal information or documentation you provide, with its subsidiaries and affiliated companies for the purpose of considering you for other available positions. L3Harris Technologies is an E-Verify Employer. Please click here for the E-Verify Poster in English or Spanish. For information regarding your Right To Work, please click here for English or Spanish.
09/22/2026
Full time
L3Harris is dedicated to recruiting and developing high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers' mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do. L3Harris is the Trusted Disruptor in defense tech. With customers' mission-critical needs always in mind, our employees deliver end-to-end technology solutions connecting the space, air, land, sea and cyber domains in the interest of national security. Job Title: Senior Specialist, Integration & Test Engineer Job Code: 42447 Job Location: Melbourne, Florida Job Schedule: 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked, and have every other Friday off Job Description: L3Harris Intelligence & Cyber Sector, within the Space and Mission Systems Segment, is seeking an experienced System Software Integration and Test Engineer to support complex cyber-resilient, cloud-based solutions across the full product lifecycle. The selected candidate will lead and support system integration and test activities, including requirements analysis for testability, test architecture development, integration planning, verification execution, anomaly resolution, and production support, while developing and executing test plans, procedures, and integration flows for subsystems, lower-level assemblies, and end-to-end First Article testing. Additional responsibilities include coordinating integration activities across test beds, hardware/software-in-the-loop environments, and software simulators developed internally and by subcontractors. The engineer will define and implement verification strategies, support requirements traceability and compliance, evaluate subsystem- and system-level performance, and collaborate cross-functionally with systems engineering, software engineering, quality, operations, and external partners to resolve technical issues and ensure successful execution of system-level integration and verification objectives. The ideal candidate will have experience with complex system integration, aerospace or spacecraft test environments, and structured verification and validation processes. Essential Functions: Oversee the integration and testing of lower-level software components through subsystem and application-level verification. Develop and maintain test documentation, including Test Requirements Documents, Test Design Documents (TDDs), Test Plans, and test procedures. Support and direct personnel in the execution of secure software solutions, including vulnerability scanning, secure interface verification, continuous update testing, and compliance documentation validation prior to release. Develop and execute functional, performance, integration, and qualification test procedures, and document results to verify compliance with program requirements. Support test environment setup, script development, test procedure development, implementation, checkout of software test platforms, and evaluation of analysis tools, as required. Identify, document, track, and assist in resolving software integration and test issues through closure. Analyze test results, identify anomalies, and collaborate with development teams to determine root cause and support corrective actions. Represent Software Integration and Test in major technical reviews, including SRR, SDR, PDR, CDR, and TRR. Partner with cross-functional teams, including Systems Engineering, Project Engineering, Cybersecurity, and Software Engineering, during requirements analysis and verification planning, including development and maintenance of the Requirements Verification Traceability Matrix (RVTM). Support secure software deployment activities and ensure verification of software baselines, interfaces, and configuration changes. Work extended and weekend hours, as needed, during critical program integration and test phases. Be available to travel up to 10%, as required. Qualifications: Bachelor's Degree and minimum 6 years of prior relevant experience. Graduate Degree and a minimum of 4 years of prior related experience. In lieu of a degree, minimum of 10 years of prior related experience. Active TS/SCI clearance. Preferred Additional Skills: 2+ years of network administration experience including configuration of firewalls, VPNs, zero-trust models in support of software-defined cloud networking. 2+ years with CRA Software integration, testing, and troubleshooting. Experience working on defense systems, including space payloads, spacecraft buses, ground systems, and environmental testing. Experience with the five pillars of cyber resilience; prepare/identify, protect, detect, respond, and recover. Experience with hardware and software requirements testability, requirements definition, block diagrams, interconnect diagrams, and hardware/software integration. Experience using DOORS and/or MBSE tools such as Cameo and Magic Draw are a plus. Experience with automation and scripting languages such as Java, Python, and Perl. Experience with Jira, Bitbucket, Confluence, and source control tools. Hands-on experience with RF test and measurement equipment, including modems, emulators, spectrum analyzers, network analyzers, logic analyzers, signal generators, oscilloscopes, and power sensors, in support of integration, verification, and system performance evaluation. L3Harris Technologies is proud to be an Equal Opportunity Employer. L3Harris is committed to treating all employees and applicants for employment with respect and dignity and maintaining a workplace that is free from unlawful discrimination. All applicants will be considered for employment without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender (including pregnancy, childbirth, breastfeeding or other related medical conditions), gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, characteristic or membership in any other group protected by federal, state or local laws. L3Harris maintains a drug-free workplace and performs pre-employment substance abuse testing and background checks, where permitted by law. Please be aware many of our positions require the ability to obtain a security clearance. Security clearances may only be granted to U.S. citizens. In addition, applicants who accept a conditional offer of employment may be subject to government security investigation(s) and must meet eligibility requirements for access to classified information. By submitting your resume for this position, you understand and agree that L3Harris Technologies may share your resume, as well as any other related personal information or documentation you provide, with its subsidiaries and affiliated companies for the purpose of considering you for other available positions. L3Harris Technologies is an E-Verify Employer. Please click here for the E-Verify Poster in English or Spanish. For information regarding your Right To Work, please click here for English or Spanish.
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).
09/22/2026
Full time
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 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 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).
09/22/2026
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/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 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/22/2026
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 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. McLean, VA: $197,300 - $225,100 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).
09/22/2026
Full time
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/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. McLean, VA: $197,300 - $225,100 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).