Intro Are you ready to explore a world of possibilities, both at work and duringyour time off? Join our American Airlines family, and you'll travel the world, grow your expertise and become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board! Why you'll love this job As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. The Software domain refers to the area within Information Technology that focuses on the development, deployment, management, and maintenance of software applications that support business processes and user needs. This includes development, application lifecycle management, requirement analysis, QA, security & compliance, and maintaining the applications and infrastructure. What you'll do As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations. Writes, tests, and documents technical work products (e.g., code, scripts, processes) according to organizational standards and practices Consistently produces good quality technical work products that are clear, concise, tested, and easily understood by others Efficiently debugs design-time and run-time problems and effectively identifies problems in dependencies or caused by interactions with other services Designs new implementations and provides enhancements to existing architectures, maintaining reliability, resiliency, security, and performance Identifies and corrects issues with system components affecting operational reliability, stability and performance based on observable telemetry Understands and follows secure coding practices to avoid known potential vulnerabilities and actively looks for vulnerabilities during code reviews Identifies opportunities for automation that improve team performance and raises them to the team Consistently identifies and capitalizes on opportunities for simplification All you'll need for success Minimum Qualifications- Education & Prior Job Experience Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 1+ years of experience designing, developing, and implementing large-scale solutions in production environments Preferred Qualifications- Education & Prior Job Experience Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training Airline Industry experience Skills, Licenses & Certifications Experience with the following technologies: Programming Languages: Java, Python, C#, Javascript/Typescript Frameworks: Spring/SpringBoot, FastAPI Front End Technologies: Angular/React Deployment Technologies: Kubernetes, Docker Source Control: GitHub, Azure DevOps CICD: GitHub Actions, Azure DevOps Data management: PostgreSQL, MongoDB, Redis Integration/APIs Technologies: Kafka, REST, GraphQL Cloud Providers such as Azure and AWS Test Automation: Selenium, TestNG, Postman, SonarQube, Cypress, JUnit/NUnit/PyTest, Cucumber, Playwright, Wiremock/Mockito/Moq Ability to concisely convey ideas verbally, in writing, in code, and in diagrams Experience in Agile methodologies, such as SCRUM Experience in DevOps Toolchain methodologies, including Continuous Integration and Continuous Deployment Familiarity with modern AI development practices, including spec-driven development, AI- assited coding tools, and critical review of AI-generated code What you'll get Feel free to take advantage of all that American Airlines has to offer: Travel Perks: Ready to explore the world? You, your family and your friends can reach 365 destinations on more than 6,800 daily flights across our global network. Health Benefits: On day one, you'll have access to your health, dental, prescription and vision benefits to help you stay well. And that's just the start, we also offer virtual doctor visits, flexible spending accounts and more. Wellness Programs: We want you to be the best version of yourself - that's why our wellness programs provide you with all the right tools, resources and support you need. 401(k) Program: Available upon hire and, depending on the workgroup, employer contributions to your 401(k) program are available after one year. Additional Benefits: Other great benefits include our Employee Assistance Program, pet insurance and discounts on hotels, cars, cruises and more Feel free to be yourself at American From the team members we hire to the customers we serve, inclusion and diversity are the foundation of the dynamic workforce at American Airlines. Our 20+ Team Member Business Resource Groups are focused on connecting our team members to our customers, suppliers, communities and shareholders, helping team members reach their full potential and creating an inclusive work environment to meet and exceed the needs of our diverse world. Are you ready to feel a tremendous sense of pride and satisfaction as you do your part to keep the largest airline in the world running smoothly as we care for people on life's journey? Feel free to be yourself at American.
11/12/2026
Full time
Intro Are you ready to explore a world of possibilities, both at work and duringyour time off? Join our American Airlines family, and you'll travel the world, grow your expertise and become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board! Why you'll love this job As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. The Software domain refers to the area within Information Technology that focuses on the development, deployment, management, and maintenance of software applications that support business processes and user needs. This includes development, application lifecycle management, requirement analysis, QA, security & compliance, and maintaining the applications and infrastructure. What you'll do As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations. Writes, tests, and documents technical work products (e.g., code, scripts, processes) according to organizational standards and practices Consistently produces good quality technical work products that are clear, concise, tested, and easily understood by others Efficiently debugs design-time and run-time problems and effectively identifies problems in dependencies or caused by interactions with other services Designs new implementations and provides enhancements to existing architectures, maintaining reliability, resiliency, security, and performance Identifies and corrects issues with system components affecting operational reliability, stability and performance based on observable telemetry Understands and follows secure coding practices to avoid known potential vulnerabilities and actively looks for vulnerabilities during code reviews Identifies opportunities for automation that improve team performance and raises them to the team Consistently identifies and capitalizes on opportunities for simplification All you'll need for success Minimum Qualifications- Education & Prior Job Experience Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 1+ years of experience designing, developing, and implementing large-scale solutions in production environments Preferred Qualifications- Education & Prior Job Experience Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training Airline Industry experience Skills, Licenses & Certifications Experience with the following technologies: Programming Languages: Java, Python, C#, Javascript/Typescript Frameworks: Spring/SpringBoot, FastAPI Front End Technologies: Angular/React Deployment Technologies: Kubernetes, Docker Source Control: GitHub, Azure DevOps CICD: GitHub Actions, Azure DevOps Data management: PostgreSQL, MongoDB, Redis Integration/APIs Technologies: Kafka, REST, GraphQL Cloud Providers such as Azure and AWS Test Automation: Selenium, TestNG, Postman, SonarQube, Cypress, JUnit/NUnit/PyTest, Cucumber, Playwright, Wiremock/Mockito/Moq Ability to concisely convey ideas verbally, in writing, in code, and in diagrams Experience in Agile methodologies, such as SCRUM Experience in DevOps Toolchain methodologies, including Continuous Integration and Continuous Deployment Familiarity with modern AI development practices, including spec-driven development, AI- assited coding tools, and critical review of AI-generated code What you'll get Feel free to take advantage of all that American Airlines has to offer: Travel Perks: Ready to explore the world? You, your family and your friends can reach 365 destinations on more than 6,800 daily flights across our global network. Health Benefits: On day one, you'll have access to your health, dental, prescription and vision benefits to help you stay well. And that's just the start, we also offer virtual doctor visits, flexible spending accounts and more. Wellness Programs: We want you to be the best version of yourself - that's why our wellness programs provide you with all the right tools, resources and support you need. 401(k) Program: Available upon hire and, depending on the workgroup, employer contributions to your 401(k) program are available after one year. Additional Benefits: Other great benefits include our Employee Assistance Program, pet insurance and discounts on hotels, cars, cruises and more Feel free to be yourself at American From the team members we hire to the customers we serve, inclusion and diversity are the foundation of the dynamic workforce at American Airlines. Our 20+ Team Member Business Resource Groups are focused on connecting our team members to our customers, suppliers, communities and shareholders, helping team members reach their full potential and creating an inclusive work environment to meet and exceed the needs of our diverse world. Are you ready to feel a tremendous sense of pride and satisfaction as you do your part to keep the largest airline in the world running smoothly as we care for people on life's journey? Feel free to be yourself at American.
Job Description Job Description Job Title: Senior Systems Engineering Technician Department: Engineering Reports to: Team Lead - Systems Engineering Location: 4 Sunshine Blvd, Ormond Beach, FL 32174 Work Schedule: Full-time, salaried exempt; occasional travel for installation or commissioning support; overtime may be required Role purpose The Senior Systems Engineering Technician leads the control documentation, programming and test work on complex jobs, writes Germfree controls drafting, install and test standards, and checks the work of junior technicians. The role works with minimal direction, bringing design decisions to an engineer for approval. Germfree Engineering designs the products the plant builds: containment and aseptic equipment (biosafety cabinets, isolators, gloveboxes, laminar flow workstations, pass-throughs) and turnkey modular and mobile facilities (BSL-2 to BSL-4 biocontainment labs, cGMP cleanrooms and compounding pharmacies) with integrated HVAC, electrical, plumbing and controls. Much of the work is engineered-to-order for regulated customers, so designs must be buildable in the Ormond Beach plant, code-compliant, and documented well enough to pass customer and certifier review. Systems Engineering Technicians are controls design and test technicians. They produce the panel layouts, wiring diagrams, harness documents and bills of material for Germfree control and low-voltage systems - PLCs and smart relays, VFD/motor controls, the building management system (BMS), HMIs, access control, fire and security, CCTV and network hardware - and they program, configure and bench-test those systems from engineer-written sequences and Germfree templates. The difference from the engineer track is ownership of the engineering judgment: technicians build, configure and test to the sequence of operations, alarm list and Germfree standards, while the control architecture, sequence of operations, basis of design, containment interlock and alarm philosophy, and network and cybersecurity design sit with an engineer. Senior technicians carry practical know-how about how Germfree control systems really get built and started up - the panel, harness, network and startup details that don't show in a sequence of operations. They are the go-to person when a system must be wired, communicate, and work on the floor the first time. What success looks like Everyone at Germfree is reviewed on the same four expectations - Performance, Technical Proficiency, Credit & Accountability, and Communication & Conflict - judged against this rung, not against other people. Performance. Works accurately, keeps rework low, hits schedule and picks up cross-training. For a T3 that means complex control packages delivered without rework, improved drafting, install and test standards in use, and junior technicians developing under their guidance. Technical Proficiency. Meets the technical proficiency list below on their own. Credit & Accountability. Owns complex outcomes end to end and never shifts blame; makes the people they mentor look good. Communication & Conflict. Explains issues clearly across cross-functional teams; handles tense moments early and calmly. The two teamwork expectations stand on their own - strength in one does not make up for falling short on the other. Year-one accomplishments Leads the control documentation and test work of a complex job - multi-module facility, mobile lab or custom equipment - through FAT. Publishes a Germfree panel, install or test standard, template or symbol library. Has begun elevating the team - junior technicians producing work with fewer checker comments. Key responsibilities Own complex control packages Lead the control documentation, programming and test work on complex jobs - multi-module facilities, mobile labs and custom equipment - from the engineer's sequence of operations to FAT. Interpret client requirements with the engineer and communicate design objectives to the Systems team and project management. Provide production support and advanced programming of motor-control drive systems. Own software conformance and check that installed hardware and network infrastructure meet client requirements, with engineer approval. Standards and quality Develop and maintain Germfree panel, wiring, harness and install standards, templates, symbol libraries and test procedures. Check T1-T2 work before release; review redlines, ECRs and ECNs for consistency with production methods. Lead root cause when build or test issues trace back to documentation, wiring or programming, with audits and cross-functional follow-through. Project and build Track control-package milestones and deadlines; flag schedule risk early and help balance resources. Review facility balancing and calibration results with the engineer and help resolve difficult scenarios. Support CQV during FAT and commissioning on complex jobs. Develop others Mentor T1-T2 technicians and junior engineers on Germfree controls build and test practice. Scope of this level Area Expectation at this level Direction received Minimal; checks with an engineer on design decisions. Work complexity Complete control packages for complex and custom jobs. Problem solving Solves complex wiring, communication and test problems. Influence on others Technical guide for technicians; mentors junior engineers on build and test. Technical proficiency What fully doing this rung means: Delivers a control package for a multi-module or custom job that builds and passes FAT without drafting or programming-error changes. Diagnoses intermittent BACnet, Modbus and network communication faults on mixed-vendor systems. Reads room pressurization and airflow results well enough to support balancing and spot control-side causes. Manages XREFs and produces the right SD, DD and FD drawing sets in AutoCAD. Writes drafting, install and test standards others can follow. Matrix targets: AutoCAD 3 Airflow Balancing 1 GF Product Knowledge 2 cGMP/BMBL 1 Project Management 2 Technical Writing 2 MS Office 2. Qualifications Associate degree or technical diploma in electrical, electronics, controls or instrumentation technology, or similar; or equivalent field experience in electrical control systems. 6-10 years of controls or electrical design experience. Proficient PLC, smart-relay, VFD and HMI programming (IDEC, Keyence, Allen-Bradley, or similar). Detailed BACnet and Modbus experience, including defining methods and troubleshooting problem systems in a support role. Fluent in AutoCAD 2D; strong drafting. Experienced with electrical construction and assembly methods to develop install standards. Intermediate understanding of ventilation and HVAC. Proficient with project tracking, milestones and deadlines; mentors others. Preferred experience BMS front-end programming, including exposure to structured text (IEC 61131-3). Biocontainment, cleanroom or pharmaceutical facility controls experience. Experience with emergency vehicles, coaches or boats. Solid Edge or other 3D design software. Tools and standards Tools: AutoCAD, PLC, HMI, drive and BMS software, BACnet, Modbus and network diagnostic tools, Global Shop Solutions ERP, Microsoft Office, test instruments. Standards: Germfree controls drafting, install and test standards (contributor); UL 508A; NEC/NFPA 70; NFPA 70E; NFPA 72; BACnet (ASHRAE 135) and Modbus; ISA-5.1 symbols. Core capabilities Top five traits, ranked: 1 Analytical Skills 2 Precision / Attention to Detail 3 Teamwork 4 Problem Solver 5 Tenacity. Core values: Grit, Ownership, Innovation, Integrity. Work environment Office environment with regular time on the production floor, at test benches and in test areas. Extended computer, CAD and programming work; occasional lifting up to 25 lbs. Required PPE on the production floor; electrical safe-work and lockout/tagout practices per NFPA 70E. Occasional travel for installation or commissioning support. Overtime may be required. Growth path Staff Systems Engineering Technician (T4). Promotion is based on consistently doing next-rung work, separate from the annual review. Technicians who complete an engineering degree may move to the engineer track. Supervision Required: Minimal - Works independently and checks with an engineer on design decisions. Supervisory Responsibilities: None. Checks T1-T2 work and mentors technicians and junior engineers. Why You'll Love Germfree: Germfree is committed to employee well-being, growth, and work-life balance. We provide a supportive environment, strong benefits, and the tools you need to succeed. Insurance & Benefits Medical, dental, and vision insurance Short- and long-term disability Company-paid life insurance Optional pet insurance Pay & Financial Perks 401(k) with company match Employee referral bonuses Shoe and prescription safety-glasses reimbursements Time Off & Leave . click apply for full job details
11/12/2026
Full time
Job Description Job Description Job Title: Senior Systems Engineering Technician Department: Engineering Reports to: Team Lead - Systems Engineering Location: 4 Sunshine Blvd, Ormond Beach, FL 32174 Work Schedule: Full-time, salaried exempt; occasional travel for installation or commissioning support; overtime may be required Role purpose The Senior Systems Engineering Technician leads the control documentation, programming and test work on complex jobs, writes Germfree controls drafting, install and test standards, and checks the work of junior technicians. The role works with minimal direction, bringing design decisions to an engineer for approval. Germfree Engineering designs the products the plant builds: containment and aseptic equipment (biosafety cabinets, isolators, gloveboxes, laminar flow workstations, pass-throughs) and turnkey modular and mobile facilities (BSL-2 to BSL-4 biocontainment labs, cGMP cleanrooms and compounding pharmacies) with integrated HVAC, electrical, plumbing and controls. Much of the work is engineered-to-order for regulated customers, so designs must be buildable in the Ormond Beach plant, code-compliant, and documented well enough to pass customer and certifier review. Systems Engineering Technicians are controls design and test technicians. They produce the panel layouts, wiring diagrams, harness documents and bills of material for Germfree control and low-voltage systems - PLCs and smart relays, VFD/motor controls, the building management system (BMS), HMIs, access control, fire and security, CCTV and network hardware - and they program, configure and bench-test those systems from engineer-written sequences and Germfree templates. The difference from the engineer track is ownership of the engineering judgment: technicians build, configure and test to the sequence of operations, alarm list and Germfree standards, while the control architecture, sequence of operations, basis of design, containment interlock and alarm philosophy, and network and cybersecurity design sit with an engineer. Senior technicians carry practical know-how about how Germfree control systems really get built and started up - the panel, harness, network and startup details that don't show in a sequence of operations. They are the go-to person when a system must be wired, communicate, and work on the floor the first time. What success looks like Everyone at Germfree is reviewed on the same four expectations - Performance, Technical Proficiency, Credit & Accountability, and Communication & Conflict - judged against this rung, not against other people. Performance. Works accurately, keeps rework low, hits schedule and picks up cross-training. For a T3 that means complex control packages delivered without rework, improved drafting, install and test standards in use, and junior technicians developing under their guidance. Technical Proficiency. Meets the technical proficiency list below on their own. Credit & Accountability. Owns complex outcomes end to end and never shifts blame; makes the people they mentor look good. Communication & Conflict. Explains issues clearly across cross-functional teams; handles tense moments early and calmly. The two teamwork expectations stand on their own - strength in one does not make up for falling short on the other. Year-one accomplishments Leads the control documentation and test work of a complex job - multi-module facility, mobile lab or custom equipment - through FAT. Publishes a Germfree panel, install or test standard, template or symbol library. Has begun elevating the team - junior technicians producing work with fewer checker comments. Key responsibilities Own complex control packages Lead the control documentation, programming and test work on complex jobs - multi-module facilities, mobile labs and custom equipment - from the engineer's sequence of operations to FAT. Interpret client requirements with the engineer and communicate design objectives to the Systems team and project management. Provide production support and advanced programming of motor-control drive systems. Own software conformance and check that installed hardware and network infrastructure meet client requirements, with engineer approval. Standards and quality Develop and maintain Germfree panel, wiring, harness and install standards, templates, symbol libraries and test procedures. Check T1-T2 work before release; review redlines, ECRs and ECNs for consistency with production methods. Lead root cause when build or test issues trace back to documentation, wiring or programming, with audits and cross-functional follow-through. Project and build Track control-package milestones and deadlines; flag schedule risk early and help balance resources. Review facility balancing and calibration results with the engineer and help resolve difficult scenarios. Support CQV during FAT and commissioning on complex jobs. Develop others Mentor T1-T2 technicians and junior engineers on Germfree controls build and test practice. Scope of this level Area Expectation at this level Direction received Minimal; checks with an engineer on design decisions. Work complexity Complete control packages for complex and custom jobs. Problem solving Solves complex wiring, communication and test problems. Influence on others Technical guide for technicians; mentors junior engineers on build and test. Technical proficiency What fully doing this rung means: Delivers a control package for a multi-module or custom job that builds and passes FAT without drafting or programming-error changes. Diagnoses intermittent BACnet, Modbus and network communication faults on mixed-vendor systems. Reads room pressurization and airflow results well enough to support balancing and spot control-side causes. Manages XREFs and produces the right SD, DD and FD drawing sets in AutoCAD. Writes drafting, install and test standards others can follow. Matrix targets: AutoCAD 3 Airflow Balancing 1 GF Product Knowledge 2 cGMP/BMBL 1 Project Management 2 Technical Writing 2 MS Office 2. Qualifications Associate degree or technical diploma in electrical, electronics, controls or instrumentation technology, or similar; or equivalent field experience in electrical control systems. 6-10 years of controls or electrical design experience. Proficient PLC, smart-relay, VFD and HMI programming (IDEC, Keyence, Allen-Bradley, or similar). Detailed BACnet and Modbus experience, including defining methods and troubleshooting problem systems in a support role. Fluent in AutoCAD 2D; strong drafting. Experienced with electrical construction and assembly methods to develop install standards. Intermediate understanding of ventilation and HVAC. Proficient with project tracking, milestones and deadlines; mentors others. Preferred experience BMS front-end programming, including exposure to structured text (IEC 61131-3). Biocontainment, cleanroom or pharmaceutical facility controls experience. Experience with emergency vehicles, coaches or boats. Solid Edge or other 3D design software. Tools and standards Tools: AutoCAD, PLC, HMI, drive and BMS software, BACnet, Modbus and network diagnostic tools, Global Shop Solutions ERP, Microsoft Office, test instruments. Standards: Germfree controls drafting, install and test standards (contributor); UL 508A; NEC/NFPA 70; NFPA 70E; NFPA 72; BACnet (ASHRAE 135) and Modbus; ISA-5.1 symbols. Core capabilities Top five traits, ranked: 1 Analytical Skills 2 Precision / Attention to Detail 3 Teamwork 4 Problem Solver 5 Tenacity. Core values: Grit, Ownership, Innovation, Integrity. Work environment Office environment with regular time on the production floor, at test benches and in test areas. Extended computer, CAD and programming work; occasional lifting up to 25 lbs. Required PPE on the production floor; electrical safe-work and lockout/tagout practices per NFPA 70E. Occasional travel for installation or commissioning support. Overtime may be required. Growth path Staff Systems Engineering Technician (T4). Promotion is based on consistently doing next-rung work, separate from the annual review. Technicians who complete an engineering degree may move to the engineer track. Supervision Required: Minimal - Works independently and checks with an engineer on design decisions. Supervisory Responsibilities: None. Checks T1-T2 work and mentors technicians and junior engineers. Why You'll Love Germfree: Germfree is committed to employee well-being, growth, and work-life balance. We provide a supportive environment, strong benefits, and the tools you need to succeed. Insurance & Benefits Medical, dental, and vision insurance Short- and long-term disability Company-paid life insurance Optional pet insurance Pay & Financial Perks 401(k) with company match Employee referral bonuses Shoe and prescription safety-glasses reimbursements Time Off & Leave . click apply for full job details
Job Description Job Description Overview About M.C. Dean M.C. Dean is Building Intelligence . We design, build, operate, and maintain cyber-physical solutions for the nation's most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 9,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration. Why Join Us? Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values-agility, expertise, and trust-we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries. We are seeking a IT Systems Engineer 5 to join our Security and Electronic Systems (SES) business Unit. As part of (SES) Strategic Business Unit you will be part of a team that designs, engineers, integrates, operates and maintains electronic security services inclusive of intrusion detection, access control, biometric authentication, video surveillance, audio visual, it systems, perimeter defense and command and control systems for federal, local and commercial customers across high-growth markets. Responsibilities The position drives the design of architectural frameworks for large complex resilient systems to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. You will provide technical direction for the requirements development, design, engineering, configuration, integration, and testing of specific components of complex hardware/software systems. Specific responsibilities include: Assist with the automation and optimization of engineering processes. Perform systems engineering assessments (upgrades, system improvements, lifecycle refreshes, migrations, new deployments), develop conceptual design solutions, and create implementation work breakdown structures to drive planning and estimating. Advise on alternative and innovative approaches and conduct feasibility studies. Research, prototype, and develop integrated system capability by working closely with industry partners and OEMs to implement the latest and best-in-bread capabilities to meet customer emerging needs. Identify and document operational, functional, and technical requirements. Develop technical documentation, such as system architecture and system design documentation, functional and performance verification test plans, and technical implementation plans. Incorporate new plans, designs and systems into ongoing operations. Interact with the Government regarding Systems Engineering technical considerations and for associated problems, issues or conflicts. Conduct configuration and development activities. Lead/conduct testing against established test plans. Participate in interface definition, design, and changes to the configuration between affected groups and individuals throughout the life cycle. Review and provide input to program and contract work breakdown structure (WBS), work packages and the integrated master schedule (IMS). Review and/or approve system engineering documentation to ensure that processes and specifications meet system needs and are accurate, comprehensive, and complete. Support management and ensure the technical integrity of the system baseline over time, continually updating it as various changes are imposed on the system during the lifecycle from development through deployment and operations & maintenance. Qualifications Clearance/Citizen Type: Applicants selected will be subject to a government security investigation and must meet eligibility requirements, including U.S. Citizenship, for access to classified information; Active TS/SCI w/ polygraph clearance is required Education/Experience: Education: Systems Engineering, Electrical Engineering, Mechanical, Computer Science, or a Related Engineering Discipline. Bachelor's Degree and 10+ Years of progressive experience. Master's Degree desirable. 4+ years of experience with the provision of system solutions for physical security systems and IT solutions. Experience eliciting requirements, conducting research, designing, testing, and implementing hardware and software solutions for data center and virtual infrastructure technologies. Strong engineering experience with the following core platforms and services: VMware ESXi and vSphere. Microsoft Windows Server Deployment and Administration. Microsoft Windows Deployment and Administration. DNS, DFS, and DHCP. Windows Server Update Services (WSUS), Key Management Service (KMS) Active Directory and defining, implementing, and maintaining Group Policy. Public Key Infrastructure (PKI) and Certificate Authorities Experience virtualizing enterprise applications (Active Directory, MS SQL, RHEL, MS SharePoint, etc.). Experience developing, implementing, and maintaining highly secure and reliable solutions that meet all organizational Cybersecurity and Information Assurance requirements. Experience with API management, scripting languages including PowerShell, Python, JSON, Bash, etc. Meet DoD 8570 IAT Level-II requirements. Strong Oral, Written and Presentation Skills with the ability and experience communicating directly with customer leadership and technical stakeholders. Demonstrated background working with multidisciplinary teams. Demonstrated time management and organization skills to meet deadlines and quality objectives. Strong MS Excel, Word, PowerPoint, and Visio Skills is a plus. Desired Experience: Experience with Microsoft SCCM and Operating System Deployment (OSD). Experience administering OCSP (e.g. Axway Validation Authority, Microsoft OCSP Responder). Experience troubleshooting and optimizing the McAfee security product suite (Endpoint Security, DLP, HIPS, etc.). Large on-premise storage engineering and administration experience with 3PAR, NetApp, Dell/EMC, Pure Storage, etc. Experience designing and deploying SQL Database Infrastructure such as Microsoft SQL Server. Experience engineering and implementing data center and campus area networks and security stacks. Experience engineering and implementing platforms and services in a software-defined network environment. Experience with DoD IT security requirements including DISA STIG/SRGs. Understanding of Department of Defense standards and best practices. Vendor certifications, VMware, Cisco, Microsoft, NetApp, etc. What we offer: A collaborative team inspired by the way engineering and innovation enhance customer outcomes, improve lives, and change the world for the better. We are driven by our core values of agility, expertise, and trust. An opportunity to lead and build a business with the support of an industry-leading firm that has been in business for 75 years. Investment in your skills and expertise through a combination of professional and technical training programs, including leadership training and tuition reimbursement. Open and transparent communication with senior leadership as well as local office management. We offer an excellent benefits package including: A competitive salary Medical, dental, vision, life, and disability insurance Paid time off Tuition reimbursement 401k Retirement Plan Military Reserve pay offset Paid maternity leave Abilities: Exposure to computer screens for an extended period of time. Sitting for extended periods of time. Reach by extending hands or arms in any direction. Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard. Listen to and understand information and ideas presented through spoken words and sentences. Communicate information and ideas in speaking so others will understand. Read and understand information and ideas presented in writing. Apply general rules to specific problems to produce answers that make sense. Identify and understand the speech of another person.
11/12/2026
Full time
Job Description Job Description Overview About M.C. Dean M.C. Dean is Building Intelligence . We design, build, operate, and maintain cyber-physical solutions for the nation's most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 9,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration. Why Join Us? Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values-agility, expertise, and trust-we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries. We are seeking a IT Systems Engineer 5 to join our Security and Electronic Systems (SES) business Unit. As part of (SES) Strategic Business Unit you will be part of a team that designs, engineers, integrates, operates and maintains electronic security services inclusive of intrusion detection, access control, biometric authentication, video surveillance, audio visual, it systems, perimeter defense and command and control systems for federal, local and commercial customers across high-growth markets. Responsibilities The position drives the design of architectural frameworks for large complex resilient systems to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. You will provide technical direction for the requirements development, design, engineering, configuration, integration, and testing of specific components of complex hardware/software systems. Specific responsibilities include: Assist with the automation and optimization of engineering processes. Perform systems engineering assessments (upgrades, system improvements, lifecycle refreshes, migrations, new deployments), develop conceptual design solutions, and create implementation work breakdown structures to drive planning and estimating. Advise on alternative and innovative approaches and conduct feasibility studies. Research, prototype, and develop integrated system capability by working closely with industry partners and OEMs to implement the latest and best-in-bread capabilities to meet customer emerging needs. Identify and document operational, functional, and technical requirements. Develop technical documentation, such as system architecture and system design documentation, functional and performance verification test plans, and technical implementation plans. Incorporate new plans, designs and systems into ongoing operations. Interact with the Government regarding Systems Engineering technical considerations and for associated problems, issues or conflicts. Conduct configuration and development activities. Lead/conduct testing against established test plans. Participate in interface definition, design, and changes to the configuration between affected groups and individuals throughout the life cycle. Review and provide input to program and contract work breakdown structure (WBS), work packages and the integrated master schedule (IMS). Review and/or approve system engineering documentation to ensure that processes and specifications meet system needs and are accurate, comprehensive, and complete. Support management and ensure the technical integrity of the system baseline over time, continually updating it as various changes are imposed on the system during the lifecycle from development through deployment and operations & maintenance. Qualifications Clearance/Citizen Type: Applicants selected will be subject to a government security investigation and must meet eligibility requirements, including U.S. Citizenship, for access to classified information; Active TS/SCI w/ polygraph clearance is required Education/Experience: Education: Systems Engineering, Electrical Engineering, Mechanical, Computer Science, or a Related Engineering Discipline. Bachelor's Degree and 10+ Years of progressive experience. Master's Degree desirable. 4+ years of experience with the provision of system solutions for physical security systems and IT solutions. Experience eliciting requirements, conducting research, designing, testing, and implementing hardware and software solutions for data center and virtual infrastructure technologies. Strong engineering experience with the following core platforms and services: VMware ESXi and vSphere. Microsoft Windows Server Deployment and Administration. Microsoft Windows Deployment and Administration. DNS, DFS, and DHCP. Windows Server Update Services (WSUS), Key Management Service (KMS) Active Directory and defining, implementing, and maintaining Group Policy. Public Key Infrastructure (PKI) and Certificate Authorities Experience virtualizing enterprise applications (Active Directory, MS SQL, RHEL, MS SharePoint, etc.). Experience developing, implementing, and maintaining highly secure and reliable solutions that meet all organizational Cybersecurity and Information Assurance requirements. Experience with API management, scripting languages including PowerShell, Python, JSON, Bash, etc. Meet DoD 8570 IAT Level-II requirements. Strong Oral, Written and Presentation Skills with the ability and experience communicating directly with customer leadership and technical stakeholders. Demonstrated background working with multidisciplinary teams. Demonstrated time management and organization skills to meet deadlines and quality objectives. Strong MS Excel, Word, PowerPoint, and Visio Skills is a plus. Desired Experience: Experience with Microsoft SCCM and Operating System Deployment (OSD). Experience administering OCSP (e.g. Axway Validation Authority, Microsoft OCSP Responder). Experience troubleshooting and optimizing the McAfee security product suite (Endpoint Security, DLP, HIPS, etc.). Large on-premise storage engineering and administration experience with 3PAR, NetApp, Dell/EMC, Pure Storage, etc. Experience designing and deploying SQL Database Infrastructure such as Microsoft SQL Server. Experience engineering and implementing data center and campus area networks and security stacks. Experience engineering and implementing platforms and services in a software-defined network environment. Experience with DoD IT security requirements including DISA STIG/SRGs. Understanding of Department of Defense standards and best practices. Vendor certifications, VMware, Cisco, Microsoft, NetApp, etc. What we offer: A collaborative team inspired by the way engineering and innovation enhance customer outcomes, improve lives, and change the world for the better. We are driven by our core values of agility, expertise, and trust. An opportunity to lead and build a business with the support of an industry-leading firm that has been in business for 75 years. Investment in your skills and expertise through a combination of professional and technical training programs, including leadership training and tuition reimbursement. Open and transparent communication with senior leadership as well as local office management. We offer an excellent benefits package including: A competitive salary Medical, dental, vision, life, and disability insurance Paid time off Tuition reimbursement 401k Retirement Plan Military Reserve pay offset Paid maternity leave Abilities: Exposure to computer screens for an extended period of time. Sitting for extended periods of time. Reach by extending hands or arms in any direction. Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard. Listen to and understand information and ideas presented through spoken words and sentences. Communicate information and ideas in speaking so others will understand. Read and understand information and ideas presented in writing. Apply general rules to specific problems to produce answers that make sense. Identify and understand the speech of another person.
Job Description Job Description Overview About M.C. Dean M.C. Dean is Building Intelligence . We design, build, operate, and maintain cyber-physical solutions for the nation's most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 9,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration. Why Join Us? Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values-agility, expertise, and trust-we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries. We are seeking a IT-oriented System Engineer 3 to join our Security and Electronic Systems (SES) business Unit. As part of (SES) Strategic Business Unit you will be part of a dynamic team responsible for the design, implementation, operations & maintenance, and cybersecurity for large complex resilient hardware and virtualized infrastructure to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. Responsibilities What you'll do: The position drives the design of architectural frameworks for large complex resilient systems to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. You will provide technical direction for the requirements development, design, engineering, configuration, integration, and testing of specific components of complex hardware/software systems. Specific responsibilities include: Assist with the automation and optimization of engineering processes. Perform systems engineering assessments (upgrades, system improvements, lifecycle refreshes, migrations, new deployments), develop conceptual design solutions, and create implementation work breakdown structures to drive planning and estimating. Advise on alternative and innovative approaches and conduct feasibility studies. Support research, prototyping, and development of integrated system capability by working closely with industry partners and OEMs to implement the latest and best-in-bread capabilities to meet customer emerging needs. Support identification and documentation of operational, functional, and technical requirements. Develop technical documentation, such as system architecture and system design documentation, functional and performance verification test plans, and technical implementation plans. Incorporate new plans, designs and systems into ongoing operations. Interact with the Government regarding Systems Engineering technical considerations and for associated problems, issues or conflicts. Conduct configuration and development activities. Conduct testing against established test plans. Participate in interface definition, design, and changes to the configuration between affected groups and individuals throughout the life cycle. Review and provide input to program and contract work breakdown structure (WBS), work packages and the integrated master schedule (IMS). Support the review of system engineering documentation to ensure that processes and specifications meet system needs and are accurate, comprehensive, and complete. Support configuration management through the system development and sustainment lifecycle. Qualifications Clearance/Citizen Type: Applicants selected will be subject to a government security investigation and must meet eligibility requirements, including U.S. Citizenship, for access to classified information; Active TS/SCI with Polygraph is required Education/Experience: Education: Systems Engineering, Electrical Engineering, Mechanical, Computer Science, or a Related Engineering Discipline . Bachelor's Degree and 5+ Years of progressive experience. Master's Degree desirable. 2+ years of experience with the provision of system solutions for physical security systems and IT solutions. Experience eliciting requirements, conducting research, designing, testing, and implementing hardware and software solutions for data center and virtual infrastructure technologies. Engineering experience with some of the following core platforms and services: VMware ESXi and vSphere. Microsoft Windows Server Deployment and Administration. Microsoft Windows Deployment and Administration. DNS, DFS, and DHCP. Windows Server Update Services (WSUS), Key Management Service (KMS) Active Directory and defining, implementing, and maintaining Group Policy. Public Key Infrastructure (PKI) and Certificate Authorities Experience developing, implementing, and maintaining highly secure and reliable solutions that meet all organizational Cybersecurity and Information Assurance requirements. Experience with API management, scripting languages including PowerShell, Python, JSON, Bash, etc. Meet DoD 8570 IAT Level-II requirements. Strong Oral, Written and Presentation Skills with the ability and experience communicating directly with customer leadership and technical stakeholders. Demonstrated background working with multidisciplinary teams. Demonstrated time management and organization skills to meet deadlines and quality objectives. Strong MS Excel, Word, PowerPoint, and Visio Skills is a plus. Desired Experience: Experience virtualizing enterprise applications (Active Directory, MS SQL, RHEL, MS SharePoint, etc.). Experience with Microsoft SCCM and Operating System Deployment (OSD). Experience administering OCSP (e.g. Axway Validation Authority, Microsoft OCSP Responder). Experience troubleshooting and optimizing the McAfee security product suite (Endpoint Security, DLP, HIPS, etc.). Large on-premise storage engineering and administration experience with 3PAR, NetApp, Dell/EMC, Pure Storage, etc. Experience designing and deploying SQL Database Infrastructure such as Microsoft SQL Server. Experience engineering and implementing data center and campus area networks and security stacks. Experience engineering and implementing platforms and services in a software-defined network environment. Experience with DoD IT security requirements including DISA STIG/SRGs. Understanding of Department of Defense standards and best practices. Vendor certifications, VMware, Cisco, Microsoft, NetApp, etc. What we offer: A collaborative team inspired by the way engineering and innovation enhance customer outcomes, improve lives, and change the world for the better. We are driven by our core values of agility, expertise, and trust. An opportunity to lead and build a business with the support of an industry-leading firm that has been in business for 75 years. Investment in your skills and expertise through a combination of professional and technical training programs, including leadership training and tuition reimbursement. Open and transparent communication with senior leadership as well as local office management. We offer an excellent benefits package including: A competitive salary Medical, dental, vision, life, and disability insurance Paid time off Tuition reimbursement 401k Retirement Plan Military Reserve pay offset Paid maternity leave Abilities: Exposure to computer screens for an extended period of time. Sitting for extended periods of time. Reach by extending hands or arms in any direction. Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard. Listen to and understand information and ideas presented through spoken words and sentences. Communicate information and ideas in speaking so others will understand. Read and understand information and ideas presented in writing. Apply general rules to specific problems to produce answers that make sense. Identify and understand the speech of another person.
11/12/2026
Full time
Job Description Job Description Overview About M.C. Dean M.C. Dean is Building Intelligence . We design, build, operate, and maintain cyber-physical solutions for the nation's most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 9,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration. Why Join Us? Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values-agility, expertise, and trust-we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries. We are seeking a IT-oriented System Engineer 3 to join our Security and Electronic Systems (SES) business Unit. As part of (SES) Strategic Business Unit you will be part of a dynamic team responsible for the design, implementation, operations & maintenance, and cybersecurity for large complex resilient hardware and virtualized infrastructure to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. Responsibilities What you'll do: The position drives the design of architectural frameworks for large complex resilient systems to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. You will provide technical direction for the requirements development, design, engineering, configuration, integration, and testing of specific components of complex hardware/software systems. Specific responsibilities include: Assist with the automation and optimization of engineering processes. Perform systems engineering assessments (upgrades, system improvements, lifecycle refreshes, migrations, new deployments), develop conceptual design solutions, and create implementation work breakdown structures to drive planning and estimating. Advise on alternative and innovative approaches and conduct feasibility studies. Support research, prototyping, and development of integrated system capability by working closely with industry partners and OEMs to implement the latest and best-in-bread capabilities to meet customer emerging needs. Support identification and documentation of operational, functional, and technical requirements. Develop technical documentation, such as system architecture and system design documentation, functional and performance verification test plans, and technical implementation plans. Incorporate new plans, designs and systems into ongoing operations. Interact with the Government regarding Systems Engineering technical considerations and for associated problems, issues or conflicts. Conduct configuration and development activities. Conduct testing against established test plans. Participate in interface definition, design, and changes to the configuration between affected groups and individuals throughout the life cycle. Review and provide input to program and contract work breakdown structure (WBS), work packages and the integrated master schedule (IMS). Support the review of system engineering documentation to ensure that processes and specifications meet system needs and are accurate, comprehensive, and complete. Support configuration management through the system development and sustainment lifecycle. Qualifications Clearance/Citizen Type: Applicants selected will be subject to a government security investigation and must meet eligibility requirements, including U.S. Citizenship, for access to classified information; Active TS/SCI with Polygraph is required Education/Experience: Education: Systems Engineering, Electrical Engineering, Mechanical, Computer Science, or a Related Engineering Discipline . Bachelor's Degree and 5+ Years of progressive experience. Master's Degree desirable. 2+ years of experience with the provision of system solutions for physical security systems and IT solutions. Experience eliciting requirements, conducting research, designing, testing, and implementing hardware and software solutions for data center and virtual infrastructure technologies. Engineering experience with some of the following core platforms and services: VMware ESXi and vSphere. Microsoft Windows Server Deployment and Administration. Microsoft Windows Deployment and Administration. DNS, DFS, and DHCP. Windows Server Update Services (WSUS), Key Management Service (KMS) Active Directory and defining, implementing, and maintaining Group Policy. Public Key Infrastructure (PKI) and Certificate Authorities Experience developing, implementing, and maintaining highly secure and reliable solutions that meet all organizational Cybersecurity and Information Assurance requirements. Experience with API management, scripting languages including PowerShell, Python, JSON, Bash, etc. Meet DoD 8570 IAT Level-II requirements. Strong Oral, Written and Presentation Skills with the ability and experience communicating directly with customer leadership and technical stakeholders. Demonstrated background working with multidisciplinary teams. Demonstrated time management and organization skills to meet deadlines and quality objectives. Strong MS Excel, Word, PowerPoint, and Visio Skills is a plus. Desired Experience: Experience virtualizing enterprise applications (Active Directory, MS SQL, RHEL, MS SharePoint, etc.). Experience with Microsoft SCCM and Operating System Deployment (OSD). Experience administering OCSP (e.g. Axway Validation Authority, Microsoft OCSP Responder). Experience troubleshooting and optimizing the McAfee security product suite (Endpoint Security, DLP, HIPS, etc.). Large on-premise storage engineering and administration experience with 3PAR, NetApp, Dell/EMC, Pure Storage, etc. Experience designing and deploying SQL Database Infrastructure such as Microsoft SQL Server. Experience engineering and implementing data center and campus area networks and security stacks. Experience engineering and implementing platforms and services in a software-defined network environment. Experience with DoD IT security requirements including DISA STIG/SRGs. Understanding of Department of Defense standards and best practices. Vendor certifications, VMware, Cisco, Microsoft, NetApp, etc. What we offer: A collaborative team inspired by the way engineering and innovation enhance customer outcomes, improve lives, and change the world for the better. We are driven by our core values of agility, expertise, and trust. An opportunity to lead and build a business with the support of an industry-leading firm that has been in business for 75 years. Investment in your skills and expertise through a combination of professional and technical training programs, including leadership training and tuition reimbursement. Open and transparent communication with senior leadership as well as local office management. We offer an excellent benefits package including: A competitive salary Medical, dental, vision, life, and disability insurance Paid time off Tuition reimbursement 401k Retirement Plan Military Reserve pay offset Paid maternity leave Abilities: Exposure to computer screens for an extended period of time. Sitting for extended periods of time. Reach by extending hands or arms in any direction. Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard. Listen to and understand information and ideas presented through spoken words and sentences. Communicate information and ideas in speaking so others will understand. Read and understand information and ideas presented in writing. Apply general rules to specific problems to produce answers that make sense. Identify and understand the speech of another person.
Job Description Job Description Title: Sr. Infrastructure Engineer Location: Richmond - VA (Hybrib) Duration: 10 Months Intreview type: In Person Only NOTE: Local candidates preferred, or must be willing to relocate to Richmond, VA metro area. Will be required to come on-site 1-2 days a week after initial training and knowledge transfer. Job Description The Client is seeking an experienced Senior Infrastructure Engineer to support and enhance its hybrid infrastructure environment. The ideal candidate must possess strong technical expertise across Windows Server, cloud platforms, security, patching, automation, and production application support. This role requires in-depth and hands-on experience performing upgrades, migrations, remediation, and troubleshooting within mission-critical systems. The Senior Infrastructure Engineer will work across diverse technologies including Java, .NET, Oracle, SQL, Microsoft Dynamics, and warehouse platforms, supporting both server-level and complex production application needs. The engineer must also demonstrate strong networking knowledge, including deep familiarity with OSI layers and network protocol behavior. Preferred qualifications include Microsoft- and network-focused certifications. Key Responsibilities: Infrastructure Operations & Administration Administer, maintain, and optimize Windows Server environments across on-premises and cloud-based infrastructure. Perform OS upgrades, patch installation, testing, and ongoing system updates to ensure reliability and security. Develop and use PowerShell scripts and other automation tools to execute centralized and repetitive tasks efficiently. Lead and execute server migrations, including transitioning workloads from on-premises systems into cloud platforms. Security & Compliance Implement and maintain security configurations for servers, including endpoint protection, access control, and hardening standards. Conduct vulnerability remediation for servers and applications to maintain security compliance. Work with security tools and processes to ensure consistent protection and monitoring. Patching, Monitoring & Automation Manage patching cycles and use SCCM or similar platforms for automated patch deployment and reporting. Maintain ongoing monitoring and performance assessment of infrastructure services to identify and resolve issues proactively. Backup & Disaster Recovery Oversee routine backup operations and support recovery processes for mission-critical systems. Develop, refine, and support Disaster Recovery (DR) strategies to minimize downtime and protect data integrity. Production Application Support Provide advanced server-level support for enterprise applications using .NET, Java, SQL, Oracle, Microsoft Dynamics, and warehouse technologies. Troubleshoot high-impact production issues across hybrid infrastructure and middleware layers. Networking & Systems Integration Apply deep knowledge of OSI model layers and networking protocols to diagnose connectivity and application issues. Collaborate with cross-functional teams to support application deployments and infrastructure enhancements. Communication & Collaboration Translate business or user requests into actionable technical solutions and communicate effectively in English, both verbally and in writing. Work closely with the IT Portfolio Manager and Infrastructure & Operations teams to align engineering efforts with organizational needs. Required / Desired Skills: In-depth hands-on experience working with Windows Server in hybrid environments (on-premises and cloud). Demonstrated ability to translate user requests, provide technical support and communicate effectively in English orally and in writing In-depth hands-on experience with OS upgrades, patch installation and testing, In-depth hands-on experience with scripting utilities (PowerShell)and Windows server scripting to accomplish centralized tasks In-depth experience performing regular patching and updates to ensure system security and stability. Experience overseeing backup operations and recovery processes in mission critical environments. In-depth experience planning and executing server migrations, including moving workloads from on premises to the cloud. In-depth experience working in an environment that utilizes multiple frameworks/technologies including .NET, Java, SQL/Oracle, Microsoft Dynamics, etc In-depth experience providing server-level support and troubleshooting issues for production applications. In-depth experience managing vulnerability server and application remediation. Experience with tools like SCCM for automated patch management & deployment. Experience crafting disaster recovery (DR) plans to ensure minimal downtime and prevent data loss. Strong networking knowledge - including understanding OSI layer functionality and network protocols. Ability to work with cross-functional teams to address infrastructure needs and support application deployment. Have achieved Microsoft-focus certifications such as Azure Administrator Associate, Windows Server Hybrid Administrator Associate, etc. Has achieved network focused certifications such as Network , CCNA, etc.
11/12/2026
Full time
Job Description Job Description Title: Sr. Infrastructure Engineer Location: Richmond - VA (Hybrib) Duration: 10 Months Intreview type: In Person Only NOTE: Local candidates preferred, or must be willing to relocate to Richmond, VA metro area. Will be required to come on-site 1-2 days a week after initial training and knowledge transfer. Job Description The Client is seeking an experienced Senior Infrastructure Engineer to support and enhance its hybrid infrastructure environment. The ideal candidate must possess strong technical expertise across Windows Server, cloud platforms, security, patching, automation, and production application support. This role requires in-depth and hands-on experience performing upgrades, migrations, remediation, and troubleshooting within mission-critical systems. The Senior Infrastructure Engineer will work across diverse technologies including Java, .NET, Oracle, SQL, Microsoft Dynamics, and warehouse platforms, supporting both server-level and complex production application needs. The engineer must also demonstrate strong networking knowledge, including deep familiarity with OSI layers and network protocol behavior. Preferred qualifications include Microsoft- and network-focused certifications. Key Responsibilities: Infrastructure Operations & Administration Administer, maintain, and optimize Windows Server environments across on-premises and cloud-based infrastructure. Perform OS upgrades, patch installation, testing, and ongoing system updates to ensure reliability and security. Develop and use PowerShell scripts and other automation tools to execute centralized and repetitive tasks efficiently. Lead and execute server migrations, including transitioning workloads from on-premises systems into cloud platforms. Security & Compliance Implement and maintain security configurations for servers, including endpoint protection, access control, and hardening standards. Conduct vulnerability remediation for servers and applications to maintain security compliance. Work with security tools and processes to ensure consistent protection and monitoring. Patching, Monitoring & Automation Manage patching cycles and use SCCM or similar platforms for automated patch deployment and reporting. Maintain ongoing monitoring and performance assessment of infrastructure services to identify and resolve issues proactively. Backup & Disaster Recovery Oversee routine backup operations and support recovery processes for mission-critical systems. Develop, refine, and support Disaster Recovery (DR) strategies to minimize downtime and protect data integrity. Production Application Support Provide advanced server-level support for enterprise applications using .NET, Java, SQL, Oracle, Microsoft Dynamics, and warehouse technologies. Troubleshoot high-impact production issues across hybrid infrastructure and middleware layers. Networking & Systems Integration Apply deep knowledge of OSI model layers and networking protocols to diagnose connectivity and application issues. Collaborate with cross-functional teams to support application deployments and infrastructure enhancements. Communication & Collaboration Translate business or user requests into actionable technical solutions and communicate effectively in English, both verbally and in writing. Work closely with the IT Portfolio Manager and Infrastructure & Operations teams to align engineering efforts with organizational needs. Required / Desired Skills: In-depth hands-on experience working with Windows Server in hybrid environments (on-premises and cloud). Demonstrated ability to translate user requests, provide technical support and communicate effectively in English orally and in writing In-depth hands-on experience with OS upgrades, patch installation and testing, In-depth hands-on experience with scripting utilities (PowerShell)and Windows server scripting to accomplish centralized tasks In-depth experience performing regular patching and updates to ensure system security and stability. Experience overseeing backup operations and recovery processes in mission critical environments. In-depth experience planning and executing server migrations, including moving workloads from on premises to the cloud. In-depth experience working in an environment that utilizes multiple frameworks/technologies including .NET, Java, SQL/Oracle, Microsoft Dynamics, etc In-depth experience providing server-level support and troubleshooting issues for production applications. In-depth experience managing vulnerability server and application remediation. Experience with tools like SCCM for automated patch management & deployment. Experience crafting disaster recovery (DR) plans to ensure minimal downtime and prevent data loss. Strong networking knowledge - including understanding OSI layer functionality and network protocols. Ability to work with cross-functional teams to address infrastructure needs and support application deployment. Have achieved Microsoft-focus certifications such as Azure Administrator Associate, Windows Server Hybrid Administrator Associate, etc. Has achieved network focused certifications such as Network , CCNA, etc.
Job Description Job Description Overview About M.C. Dean M.C. Dean is Building Intelligence. We design, build, operate, and maintain cyber-physical solutions for the nation's most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 9,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration. Why Join Us? Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values-agility, expertise, and trust-we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries. We are seeking a IT-oriented IT System Engineer 3 to join our Security and Electronic Systems (SES) business Unit. As part of (SES) Strategic Business Unit you will be part of a dynamic team responsible for the design, implementation, operations & maintenance, and cybersecurity for large complex resilient hardware and virtualized infrastructure to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. Responsibilities What you'll do: The position drives the design of architectural frameworks for large complex resilient systems to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. You will provide technical direction for the requirements development, design, engineering, configuration, integration, and testing of specific components of complex hardware/software systems. Specific responsibilities include: Assist with the automation and optimization of engineering processes. Perform systems engineering assessments (upgrades, system improvements, lifecycle refreshes, migrations, new deployments), develop conceptual design solutions, and create implementation work breakdown structures to drive planning and estimating. Advise on alternative and innovative approaches and conduct feasibility studies. Support research, prototyping, and development of integrated system capability by working closely with industry partners and OEMs to implement the latest and best-in-bread capabilities to meet customer emerging needs. Support identification and documentation of operational, functional, and technical requirements. Develop technical documentation, such as system architecture and system design documentation, functional and performance verification test plans, and technical implementation plans. Incorporate new plans, designs and systems into ongoing operations. Interact with the Government regarding Systems Engineering technical considerations and for associated problems, issues or conflicts. Conduct configuration and development activities. Conduct testing against established test plans. Participate in interface definition, design, and changes to the configuration between affected groups and individuals throughout the life cycle. Review and provide input to program and contract work breakdown structure (WBS), work packages and the integrated master schedule (IMS). Support the review of system engineering documentation to ensure that processes and specifications meet system needs and are accurate, comprehensive, and complete. Support configuration management through the system development and sustainment lifecycle. Qualifications Clearance/Citizen Type: Applicants selected will be subject to a government security investigation and must meet eligibility requirements, including U.S. Citizenship, for access to classified information; Active TS/SCI with poly is required Education/Experience: Education: Systems Engineering, Electrical Engineering, Mechanical, Computer Science, or a Related Engineering Discipline (not accepting Information Management, Information Systems, or Cybersecurity degrees). Bachelor's Degree and 5+ Years of progressive experience. Master's Degree desirable. 5+ years of experience with the provision of system solutions for physical security systems and IT solutions. Experience eliciting requirements, conducting research, designing, testing, and implementing hardware and software solutions for data center and virtual infrastructure technologies. Engineering experience with some of the following core platforms and services: VMware ESXi and vSphere. Microsoft Windows Server Deployment and Administration. Microsoft Windows Deployment and Administration. DNS, DFS, and DHCP. Windows Server Update Services (WSUS), Key Management Service (KMS) Active Directory and defining, implementing, and maintaining Group Policy. Public Key Infrastructure (PKI) and Certificate Authorities Experience developing, implementing, and maintaining highly secure and reliable solutions that meet all organizational Cybersecurity and Information Assurance requirements. Experience with API management, scripting languages including PowerShell, Python, JSON, Bash, etc. Meet DoD 8570 IAT Level-II requirements. Strong Oral, Written and Presentation Skills with the ability and experience communicating directly with customer leadership and technical stakeholders. Demonstrated background working with multidisciplinary teams. Demonstrated time management and organization skills to meet deadlines and quality objectives. Strong MS Excel, Word, PowerPoint, and Visio Skills is a plus. Desired Experience: Experience virtualizing enterprise applications (Active Directory, MS SQL, RHEL, MS SharePoint, etc.). Experience with Microsoft SCCM and Operating System Deployment (OSD). Experience administering OCSP (e.g. Axway Validation Authority, Microsoft OCSP Responder). Experience troubleshooting and optimizing the McAfee security product suite (Endpoint Security, DLP, HIPS, etc.). Large on-premise storage engineering and administration experience with 3PAR, NetApp, Dell/EMC, Pure Storage, etc. Experience designing and deploying SQL Database Infrastructure such as Microsoft SQL Server. Experience engineering and implementing data center and campus area networks and security stacks. Experience engineering and implementing platforms and services in a software-defined network environment. Experience with DoD IT security requirements including DISA STIG/SRGs. Understanding of Department of Defense standards and best practices. Vendor certifications, VMware, Cisco, Microsoft, NetApp, etc. What we offer: A collaborative team inspired by the way engineering and innovation enhance customer outcomes, improve lives, and change the world for the better. We are driven by our core values of agility, expertise, and trust. An opportunity to lead and build a business with the support of an industry-leading firm that has been in business for 75 years. Investment in your skills and expertise through a combination of professional and technical training programs, including leadership training and tuition reimbursement. Open and transparent communication with senior leadership as well as local office management. We offer an excellent benefits package including: A competitive salary Medical, dental, vision, life, and disability insurance Paid time off Tuition reimbursement 401k Retirement Plan Military Reserve pay offset Paid maternity leave Abilities: Exposure to computer screens for an extended period of time. Sitting for extended periods of time. Reach by extending hands or arms in any direction. Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard. Listen to and understand information and ideas presented through spoken words and sentences. Communicate information and ideas in speaking so others will understand. Read and understand information and ideas presented in writing. Apply general rules to specific problems to produce answers that make sense. Identify and understand the speech of another person.
11/12/2026
Full time
Job Description Job Description Overview About M.C. Dean M.C. Dean is Building Intelligence. We design, build, operate, and maintain cyber-physical solutions for the nation's most mission-critical facilities, secure environments, complex infrastructure, and global enterprises. With over 9,000 employees, our capabilities span electrical, electronic security, telecommunications, life safety, automation and controls, audiovisual, and IT systems. Headquarters in Tysons, Virginia, M.C. Dean delivers resilient, secure, and innovative power and technology solutions through engineering expertise and smart systems integration. Why Join Us? Our people are passionate about engineering innovation that improves lives and drives impactful change. Guided by our core values-agility, expertise, and trust-we foster a collaborative and forward-thinking work environment. At M.C. Dean, we are committed to building the next generation of technical leaders in electrical, engineering, and cybersecurity industries. We are seeking a IT-oriented IT System Engineer 3 to join our Security and Electronic Systems (SES) business Unit. As part of (SES) Strategic Business Unit you will be part of a dynamic team responsible for the design, implementation, operations & maintenance, and cybersecurity for large complex resilient hardware and virtualized infrastructure to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. Responsibilities What you'll do: The position drives the design of architectural frameworks for large complex resilient systems to ensure implemented solutions meet stakeholder needs, standards, and performance requirements. You will provide technical direction for the requirements development, design, engineering, configuration, integration, and testing of specific components of complex hardware/software systems. Specific responsibilities include: Assist with the automation and optimization of engineering processes. Perform systems engineering assessments (upgrades, system improvements, lifecycle refreshes, migrations, new deployments), develop conceptual design solutions, and create implementation work breakdown structures to drive planning and estimating. Advise on alternative and innovative approaches and conduct feasibility studies. Support research, prototyping, and development of integrated system capability by working closely with industry partners and OEMs to implement the latest and best-in-bread capabilities to meet customer emerging needs. Support identification and documentation of operational, functional, and technical requirements. Develop technical documentation, such as system architecture and system design documentation, functional and performance verification test plans, and technical implementation plans. Incorporate new plans, designs and systems into ongoing operations. Interact with the Government regarding Systems Engineering technical considerations and for associated problems, issues or conflicts. Conduct configuration and development activities. Conduct testing against established test plans. Participate in interface definition, design, and changes to the configuration between affected groups and individuals throughout the life cycle. Review and provide input to program and contract work breakdown structure (WBS), work packages and the integrated master schedule (IMS). Support the review of system engineering documentation to ensure that processes and specifications meet system needs and are accurate, comprehensive, and complete. Support configuration management through the system development and sustainment lifecycle. Qualifications Clearance/Citizen Type: Applicants selected will be subject to a government security investigation and must meet eligibility requirements, including U.S. Citizenship, for access to classified information; Active TS/SCI with poly is required Education/Experience: Education: Systems Engineering, Electrical Engineering, Mechanical, Computer Science, or a Related Engineering Discipline (not accepting Information Management, Information Systems, or Cybersecurity degrees). Bachelor's Degree and 5+ Years of progressive experience. Master's Degree desirable. 5+ years of experience with the provision of system solutions for physical security systems and IT solutions. Experience eliciting requirements, conducting research, designing, testing, and implementing hardware and software solutions for data center and virtual infrastructure technologies. Engineering experience with some of the following core platforms and services: VMware ESXi and vSphere. Microsoft Windows Server Deployment and Administration. Microsoft Windows Deployment and Administration. DNS, DFS, and DHCP. Windows Server Update Services (WSUS), Key Management Service (KMS) Active Directory and defining, implementing, and maintaining Group Policy. Public Key Infrastructure (PKI) and Certificate Authorities Experience developing, implementing, and maintaining highly secure and reliable solutions that meet all organizational Cybersecurity and Information Assurance requirements. Experience with API management, scripting languages including PowerShell, Python, JSON, Bash, etc. Meet DoD 8570 IAT Level-II requirements. Strong Oral, Written and Presentation Skills with the ability and experience communicating directly with customer leadership and technical stakeholders. Demonstrated background working with multidisciplinary teams. Demonstrated time management and organization skills to meet deadlines and quality objectives. Strong MS Excel, Word, PowerPoint, and Visio Skills is a plus. Desired Experience: Experience virtualizing enterprise applications (Active Directory, MS SQL, RHEL, MS SharePoint, etc.). Experience with Microsoft SCCM and Operating System Deployment (OSD). Experience administering OCSP (e.g. Axway Validation Authority, Microsoft OCSP Responder). Experience troubleshooting and optimizing the McAfee security product suite (Endpoint Security, DLP, HIPS, etc.). Large on-premise storage engineering and administration experience with 3PAR, NetApp, Dell/EMC, Pure Storage, etc. Experience designing and deploying SQL Database Infrastructure such as Microsoft SQL Server. Experience engineering and implementing data center and campus area networks and security stacks. Experience engineering and implementing platforms and services in a software-defined network environment. Experience with DoD IT security requirements including DISA STIG/SRGs. Understanding of Department of Defense standards and best practices. Vendor certifications, VMware, Cisco, Microsoft, NetApp, etc. What we offer: A collaborative team inspired by the way engineering and innovation enhance customer outcomes, improve lives, and change the world for the better. We are driven by our core values of agility, expertise, and trust. An opportunity to lead and build a business with the support of an industry-leading firm that has been in business for 75 years. Investment in your skills and expertise through a combination of professional and technical training programs, including leadership training and tuition reimbursement. Open and transparent communication with senior leadership as well as local office management. We offer an excellent benefits package including: A competitive salary Medical, dental, vision, life, and disability insurance Paid time off Tuition reimbursement 401k Retirement Plan Military Reserve pay offset Paid maternity leave Abilities: Exposure to computer screens for an extended period of time. Sitting for extended periods of time. Reach by extending hands or arms in any direction. Have finger dexterity in order to manipulate objects with fingers rather than whole hands or arms, for example, using a keyboard. Listen to and understand information and ideas presented through spoken words and sentences. Communicate information and ideas in speaking so others will understand. Read and understand information and ideas presented in writing. Apply general rules to specific problems to produce answers that make sense. Identify and understand the speech of another person.
Date Posted: 2026-10-19 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: DoD Clearance: Secret Security Clearance Status: Ability to obtain INTERIM U.S. government issued security clearance is required prior to start date At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedom and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. The Test Qualification Lead is responsible for planning, executing, and documenting environmental test campaigns to demonstrate compliance with system- and component-level requirements. This role ensures products meet program, customer, and industry standards through rigorous environmental qualification testing. The candidate will serve as the technical authority for environmental test methods, test readiness, anomaly resolution, and verification closure. What You Will Do Lead the planning, coordination, and execution of environmental qualification test activities, including vibration, shock, temperature, humidity, altitude, and electromagnetic environmental effects (E3). Develop environmental test plans, procedures, and reports in accordance with military/industry and program-specific requirements. Serve as the primary interface between engineering design teams, test laboratories, systems engineering, and program management for all qualification test matters. Review environmental requirements and ensure proper allocation, verification methods, and test coverage throughout the product lifecycle. Generate environmental test configurations, test setups, and instrumentation plans, ensuring accuracy and compliance with requirements. Lead Test Readiness Reviews (TRRs), ensuring configuration control, safety compliance, and procedural accuracy. Manage environmental test anomalies, perform root-cause analysis, coordinate troubleshooting, and drive corrective actions to closure. Interpret test data, assess system performance, and document results in formal reports suitable for customer delivery. Provide technical guidance on environmental qualification strategy, tailoring, and compliance approaches. Support risk management, schedule development, cost estimates, and resource planning for environmental testing activities. Mentor junior engineers and foster best practices in environmental testing and verification methodologies. Qualifications You Must Have Typically requires a Bachelor of Science in Electrical Engineering, Aerospace Engineering, Systems Engineering, Mechanical Engineering, Systems Engineering, Physics, Math or other related engineering disciplines. A minimum Five (5) of technical/engineering experience is required. Experience with environmental qualification requirements or equivalent military/industry standards (e.g., MIL-STD-810). Experience leading test activities including: Random and sine vibration, thermal and thermal-vacuum testing, temperature and humidity profiles, altitude and pressure testing, mechanical shock, and E3 (EMI/EMC, lightning, grounding, bonding). Experience with test instrumentation, data acquisition, and measurement best practices. Experience interpreting technical drawings, specifications, and requirement documents. Experience leading cross-functional teams in a fast-paced test environment. Qualifications We Prefer Master's degree in engineering or related discipline. Excellent communication and documentation skills, including technical writing and customer communication. Experience with aerospace or defense qualification programs. Familiarity with systems engineering processes (requirements verification, V&V planning, configuration management). Experience with test facilities, environmental chambers, and vibration/shock tables. Active security clearance or ability to obtain one. 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. Location: Tucson, AZ: ,-az-location 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 95,500 USD - 181,700 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/12/2026
Full time
Date Posted: 2026-10-19 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: DoD Clearance: Secret Security Clearance Status: Ability to obtain INTERIM U.S. government issued security clearance is required prior to start date At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedom and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. The Test Qualification Lead is responsible for planning, executing, and documenting environmental test campaigns to demonstrate compliance with system- and component-level requirements. This role ensures products meet program, customer, and industry standards through rigorous environmental qualification testing. The candidate will serve as the technical authority for environmental test methods, test readiness, anomaly resolution, and verification closure. What You Will Do Lead the planning, coordination, and execution of environmental qualification test activities, including vibration, shock, temperature, humidity, altitude, and electromagnetic environmental effects (E3). Develop environmental test plans, procedures, and reports in accordance with military/industry and program-specific requirements. Serve as the primary interface between engineering design teams, test laboratories, systems engineering, and program management for all qualification test matters. Review environmental requirements and ensure proper allocation, verification methods, and test coverage throughout the product lifecycle. Generate environmental test configurations, test setups, and instrumentation plans, ensuring accuracy and compliance with requirements. Lead Test Readiness Reviews (TRRs), ensuring configuration control, safety compliance, and procedural accuracy. Manage environmental test anomalies, perform root-cause analysis, coordinate troubleshooting, and drive corrective actions to closure. Interpret test data, assess system performance, and document results in formal reports suitable for customer delivery. Provide technical guidance on environmental qualification strategy, tailoring, and compliance approaches. Support risk management, schedule development, cost estimates, and resource planning for environmental testing activities. Mentor junior engineers and foster best practices in environmental testing and verification methodologies. Qualifications You Must Have Typically requires a Bachelor of Science in Electrical Engineering, Aerospace Engineering, Systems Engineering, Mechanical Engineering, Systems Engineering, Physics, Math or other related engineering disciplines. A minimum Five (5) of technical/engineering experience is required. Experience with environmental qualification requirements or equivalent military/industry standards (e.g., MIL-STD-810). Experience leading test activities including: Random and sine vibration, thermal and thermal-vacuum testing, temperature and humidity profiles, altitude and pressure testing, mechanical shock, and E3 (EMI/EMC, lightning, grounding, bonding). Experience with test instrumentation, data acquisition, and measurement best practices. Experience interpreting technical drawings, specifications, and requirement documents. Experience leading cross-functional teams in a fast-paced test environment. Qualifications We Prefer Master's degree in engineering or related discipline. Excellent communication and documentation skills, including technical writing and customer communication. Experience with aerospace or defense qualification programs. Familiarity with systems engineering processes (requirements verification, V&V planning, configuration management). Experience with test facilities, environmental chambers, and vibration/shock tables. Active security clearance or ability to obtain one. 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. Location: Tucson, AZ: ,-az-location 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 95,500 USD - 181,700 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Job Description Job Description SUMMARY OF RESPONSIBILITIES The Sr. Business Analyst possesses a strong technical skillset balanced with curiosity and business aptitude to develop a strong understanding of FirstKey Homes operations while fostering relationships with the business leaders they support. They will act as the assigned analytics partner to department leaders, building and maintaining critical reporting related to Key Performance Indicators (KPIs) across the business, executive/ board-level reporting, external reporting (e.g., ESG) and ad-hoc analyses. They will collaborate with senior leaders and cross-functional partners to inform and influence key business processes, executive decision-making, and strategy development for FirstKey Homes. The role will partner with business leaders to advise trends, model data, and design dashboards to increase effectiveness of managing departmental responsibilities, and partner with FP&A on planning, forecasting, and reporting to assist with the budgeting process. The desired candidate must exhibit strong prior experience and knowledge to navigate internal systems to compile and analyze data, interpret results, and assist with implementation of technical solutions. The candidate should be comfortable working in a fast-paced, high-growth company that requires adaptability, collaboration and responding with a sense of urgency. The ability to develop and foster strong business partnering relationships across the company, as well as strong communication and presentation skills is critical to achieve success in this role. ESSENTIAL DUTIES Assist in the collection and documentation of business leader's reporting requirements and estimates of effort level to support the design, development, and enhancement of existing KPI reporting. Build customized Power BI dashboards and reports to include key metrics, scoreboards, and ad hoc reporting. Maintain technical documents relating to database mapping and processes to sufficiently explain how source system data is represented in reporting. Produce forward-looking, insightful, and actionable performance analyses. Provide insightful business analyses and presentations (standard and ad-hoc) to and for senior leadership, which contribute to their effectiveness in managing and communicating operational performance, opportunities and issues within their functional area. Apply advanced SQL knowledge to build required datasets using existing Enterprise Data Warehouse data for use in Microsoft Power BI dashboards. Learn and use Python code and advanced Microsoft Excel to support ad-hoc data modeling. Learn about P&L statements and how operational KPIs impact P&L results. Partner and counsel with stakeholders (FP&A, Operations, Accounting) as analytics business partner to support critical companywide deliverables including annual planning, monthly operating reviews, quarterly reforecasting, and ongoing reporting. Lead and support special projects, ad-hoc analysis, and recommendations to advance FirstKey Homes strategic growth agenda, decision making and performance delivery. Identify opportunities and partner with stakeholders to develop business cases, including sensitivity modeling, for department-specific or company-wide initiatives to evaluate the viability and associated risks of business cases. ' Serve as thought leader for key business intelligence initiatives. Assist in conceptualizing and defining strategies as well as leading and coordinating efforts to operationalize concepts throughout the business. This brief summary is not an all-inclusive description of job duties. Other job duties and responsibilities may also be assigned by the incumbent's manager at any time based upon Company need. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. REQUIRED EDUCATION AND EXPERIENCE Bachelor's degree in Business, Finance, Data Analytics, or Computer Science with equivalent work experience and/or education. Minimum 2 years' experience in an analytically driven role, or advanced technical education with applicable experience. Advanced PowerPoint, Power BI, and Excel skills with focus on executive messaging. Advanced SQL proficiency. Detail-oriented with a commitment to operational excellence and quality. Experience with large datasets, recommending actions and synthetizing insights. Proven ability to manage data and extract exceptions for targeted performance management. Highly process oriented with passion to investigate root causes, driving process improvement, and enabling change management. Experience working within a multi-disciplined, cross-functional technical organization. Exceptional verbal and written communication skills with proven ability to effectively influence staff at all levels. REQUIRED SKILLS Critical Thinking - Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems. Complex Problem Solving - Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions. Mathematics - Using mathematics to solve problems. Active Listening - Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times. Active Learning - Understanding the implications of new information for both current and future problem-solving and decision-making. Systems Evaluation - Identifying measures or indicators of system performance and the actions needed to improve or correct performance, relative to the goals of the system. Monitoring - Monitoring/Assessing performance of yourself, other individuals, or organizations to make improvements or take corrective action. Speaking - Talking to others to convey information effectively. Writing - Communicating effectively in writing as appropriate for the needs of the audience. PREFERRED EDUCATION AND EXPERIENCE Experience working in property management, real estate or similar industry Experience working in a fast pace, high growth company. Familiar with HTML and/or JavaScript. Familiar with Azure services such as Microsoft Data Factory / Fabric, Data Lakes, or similar ETL. Comfort reviewing financial statements (P&L) and ability to tie operational KPIs to P&L outcomes. Experience with Python for data modeling. WORK STYLES & BEHAVIORS Leadership - Job requires a willingness to lead, take charge, and offer opinions and direction. Analytical Thinking - Job requires analyzing information and using logic to address work-related issues and problems. Attention to Detail - Job requires being careful about detail and thorough in completing work tasks. Initiative - Job requires a willingness to take on responsibilities and challenges. Cooperation - Job requires being pleasant with others on the job and displaying a good-natured, cooperative attitude. Integrity - Job requires being honest and ethical. Adaptability/Flexibility - Job requires being open to change (positive or negative) and to considerable variety in the workplace. FirstKey Homes is an equal opportunity employer and will not tolerate discrimination in employment on the basis of race, color, age, sex, sexual orientation, gender identity or expression, religion, disability, ethnicity, national origin, marital status, veteran status, genetic information or any other legally protected classification or status.
11/11/2026
Full time
Job Description Job Description SUMMARY OF RESPONSIBILITIES The Sr. Business Analyst possesses a strong technical skillset balanced with curiosity and business aptitude to develop a strong understanding of FirstKey Homes operations while fostering relationships with the business leaders they support. They will act as the assigned analytics partner to department leaders, building and maintaining critical reporting related to Key Performance Indicators (KPIs) across the business, executive/ board-level reporting, external reporting (e.g., ESG) and ad-hoc analyses. They will collaborate with senior leaders and cross-functional partners to inform and influence key business processes, executive decision-making, and strategy development for FirstKey Homes. The role will partner with business leaders to advise trends, model data, and design dashboards to increase effectiveness of managing departmental responsibilities, and partner with FP&A on planning, forecasting, and reporting to assist with the budgeting process. The desired candidate must exhibit strong prior experience and knowledge to navigate internal systems to compile and analyze data, interpret results, and assist with implementation of technical solutions. The candidate should be comfortable working in a fast-paced, high-growth company that requires adaptability, collaboration and responding with a sense of urgency. The ability to develop and foster strong business partnering relationships across the company, as well as strong communication and presentation skills is critical to achieve success in this role. ESSENTIAL DUTIES Assist in the collection and documentation of business leader's reporting requirements and estimates of effort level to support the design, development, and enhancement of existing KPI reporting. Build customized Power BI dashboards and reports to include key metrics, scoreboards, and ad hoc reporting. Maintain technical documents relating to database mapping and processes to sufficiently explain how source system data is represented in reporting. Produce forward-looking, insightful, and actionable performance analyses. Provide insightful business analyses and presentations (standard and ad-hoc) to and for senior leadership, which contribute to their effectiveness in managing and communicating operational performance, opportunities and issues within their functional area. Apply advanced SQL knowledge to build required datasets using existing Enterprise Data Warehouse data for use in Microsoft Power BI dashboards. Learn and use Python code and advanced Microsoft Excel to support ad-hoc data modeling. Learn about P&L statements and how operational KPIs impact P&L results. Partner and counsel with stakeholders (FP&A, Operations, Accounting) as analytics business partner to support critical companywide deliverables including annual planning, monthly operating reviews, quarterly reforecasting, and ongoing reporting. Lead and support special projects, ad-hoc analysis, and recommendations to advance FirstKey Homes strategic growth agenda, decision making and performance delivery. Identify opportunities and partner with stakeholders to develop business cases, including sensitivity modeling, for department-specific or company-wide initiatives to evaluate the viability and associated risks of business cases. ' Serve as thought leader for key business intelligence initiatives. Assist in conceptualizing and defining strategies as well as leading and coordinating efforts to operationalize concepts throughout the business. This brief summary is not an all-inclusive description of job duties. Other job duties and responsibilities may also be assigned by the incumbent's manager at any time based upon Company need. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. REQUIRED EDUCATION AND EXPERIENCE Bachelor's degree in Business, Finance, Data Analytics, or Computer Science with equivalent work experience and/or education. Minimum 2 years' experience in an analytically driven role, or advanced technical education with applicable experience. Advanced PowerPoint, Power BI, and Excel skills with focus on executive messaging. Advanced SQL proficiency. Detail-oriented with a commitment to operational excellence and quality. Experience with large datasets, recommending actions and synthetizing insights. Proven ability to manage data and extract exceptions for targeted performance management. Highly process oriented with passion to investigate root causes, driving process improvement, and enabling change management. Experience working within a multi-disciplined, cross-functional technical organization. Exceptional verbal and written communication skills with proven ability to effectively influence staff at all levels. REQUIRED SKILLS Critical Thinking - Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems. Complex Problem Solving - Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions. Mathematics - Using mathematics to solve problems. Active Listening - Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times. Active Learning - Understanding the implications of new information for both current and future problem-solving and decision-making. Systems Evaluation - Identifying measures or indicators of system performance and the actions needed to improve or correct performance, relative to the goals of the system. Monitoring - Monitoring/Assessing performance of yourself, other individuals, or organizations to make improvements or take corrective action. Speaking - Talking to others to convey information effectively. Writing - Communicating effectively in writing as appropriate for the needs of the audience. PREFERRED EDUCATION AND EXPERIENCE Experience working in property management, real estate or similar industry Experience working in a fast pace, high growth company. Familiar with HTML and/or JavaScript. Familiar with Azure services such as Microsoft Data Factory / Fabric, Data Lakes, or similar ETL. Comfort reviewing financial statements (P&L) and ability to tie operational KPIs to P&L outcomes. Experience with Python for data modeling. WORK STYLES & BEHAVIORS Leadership - Job requires a willingness to lead, take charge, and offer opinions and direction. Analytical Thinking - Job requires analyzing information and using logic to address work-related issues and problems. Attention to Detail - Job requires being careful about detail and thorough in completing work tasks. Initiative - Job requires a willingness to take on responsibilities and challenges. Cooperation - Job requires being pleasant with others on the job and displaying a good-natured, cooperative attitude. Integrity - Job requires being honest and ethical. Adaptability/Flexibility - Job requires being open to change (positive or negative) and to considerable variety in the workplace. FirstKey Homes is an equal opportunity employer and will not tolerate discrimination in employment on the basis of race, color, age, sex, sexual orientation, gender identity or expression, religion, disability, ethnicity, national origin, marital status, veteran status, genetic information or any other legally protected classification or status.
Job Description Job Description Hello, "Join GD Resources for dynamic opportunities in business management and IT, where innovation meets excellence." About the Company: GD Resources is a Veteran Women-Owned Business Management and Information Technology company committed to excellence. GD Resources provides dynamic opportunities for veterans and professionals alike to contribute to innovative projects and drive success in a collaborative and supportive environment. Join us to make a difference, advance your career, and grow with a company that values integrity, diversity, and continuous improvement. Experience8-12 YearsClientNew York City - DoITTDuration6 MonthsPrimary SkillsIOS, Android, JIRA, azure, Product Manager, Trello, DevOpLocation Brooklyn, NY, 11201 Job Start Date2026-05-04Remote JobNoRequired Hours/Week35Job TypeContract Public Job TitleMid Level - Mobile App Developer (iOS & Android)Public Job DescriptionNYC Office of Technology and Innovation Job Title: Mid Level - Mobile App Developer (iOS & Android) Duration: 6+ Months with possible extension Location: 15 Metrotech Center, Brooklyn, NY 11201 Position Type: Contract Interview Type: Webcam/In-person Note: Normal Business Hours, Monday through Friday (not including a mandatory unpaid meal break after 6 hours of work), 35 work hours per week. If the consultant works more than 35 hours per week, the consultant must request overtime in the Agency's timekeeping system, and the project manager must approve those hours worked above the weekly maximum. SCOPE OF SERVICES: The developer will be responsible for overseeing the end-to-end technical execution of the new features in the NYC Secure App on iOS and Android and development of other digital resources as needed. The developer will deliver a scalable, privacy-centric systems that integrates with existing NYC data services, workflows, and web platforms. Job Description: The NYC Office of Technology and Innovation has been tasked with re-designing the NYC Secure App and an associated campaign to provide New Yorkers with a comprehensive set of tools and resources to prevent scam phone calls and text messages, educate vulnerable New Yorkers on prevention, and support New Yorkers with the resources they need when they have been victimized. Each year New Yorkers lose an estimated $6.5B to online and phone based scams, yet the city provides no systematic approach to protecting residents - this project will develop the technology and strategy to address that gap across OTI's programs including Cybersecurity, 311, and Digital Equity. TASKS: Develop quality code that is well-documented, testable, and production-ready Be proactive and seek feedback to ensure best practice solutions that meet business needs Building web solutions that are scalable and secure and align with overall city digital architecture Write and conduct unit testing as agreed with the City Engineering leads. Communicate technical decisions, needs, and priorities to engineers, product managers, and designers as part of a user-centered agile product delivery team Design the core logic with the existing vendor for the mobile application on iOS and Android to provide scam and spam protection for calls and texts. Build a responsive, accessible frontends resource sites that ensures a consistent experience across all browser types and mobile devices and leverages the NYC Design System. Apply rigorous industry-standard privacy and security standards and protocols to ensure that all user data remains private and secure. Develop the technical bridges necessary to route digital reporting data into existing intake and reporting systems. If necessary, learn new programming languages or frameworks, with help from City Engineering leads, to complete software development and testing tasks. Attend, participate, and assist in architecture, approach, and technical strategies as appropriate and requested by City Engineering leads. Mandatory Skills: At least 4 years of experience as a software engineer or application developer Experience building responsive websites with full-stack expertise Experience collaborating with product designers on cross-functional teams to ensure the best user experience. Experience working with Git based workflows Experience working in story-based workflows (e.g., Azure DevOps, JIRA, Trello, or other story or kanban-style workflow) Experience leading technical design and writing implementation planning documents Strong verbal and written communication skills Regards, Srikanth (Sri) Senior Recruiter Phone: Email: Powered by JazzHR I8bEmzW0Mq
11/06/2026
Full time
Job Description Job Description Hello, "Join GD Resources for dynamic opportunities in business management and IT, where innovation meets excellence." About the Company: GD Resources is a Veteran Women-Owned Business Management and Information Technology company committed to excellence. GD Resources provides dynamic opportunities for veterans and professionals alike to contribute to innovative projects and drive success in a collaborative and supportive environment. Join us to make a difference, advance your career, and grow with a company that values integrity, diversity, and continuous improvement. Experience8-12 YearsClientNew York City - DoITTDuration6 MonthsPrimary SkillsIOS, Android, JIRA, azure, Product Manager, Trello, DevOpLocation Brooklyn, NY, 11201 Job Start Date2026-05-04Remote JobNoRequired Hours/Week35Job TypeContract Public Job TitleMid Level - Mobile App Developer (iOS & Android)Public Job DescriptionNYC Office of Technology and Innovation Job Title: Mid Level - Mobile App Developer (iOS & Android) Duration: 6+ Months with possible extension Location: 15 Metrotech Center, Brooklyn, NY 11201 Position Type: Contract Interview Type: Webcam/In-person Note: Normal Business Hours, Monday through Friday (not including a mandatory unpaid meal break after 6 hours of work), 35 work hours per week. If the consultant works more than 35 hours per week, the consultant must request overtime in the Agency's timekeeping system, and the project manager must approve those hours worked above the weekly maximum. SCOPE OF SERVICES: The developer will be responsible for overseeing the end-to-end technical execution of the new features in the NYC Secure App on iOS and Android and development of other digital resources as needed. The developer will deliver a scalable, privacy-centric systems that integrates with existing NYC data services, workflows, and web platforms. Job Description: The NYC Office of Technology and Innovation has been tasked with re-designing the NYC Secure App and an associated campaign to provide New Yorkers with a comprehensive set of tools and resources to prevent scam phone calls and text messages, educate vulnerable New Yorkers on prevention, and support New Yorkers with the resources they need when they have been victimized. Each year New Yorkers lose an estimated $6.5B to online and phone based scams, yet the city provides no systematic approach to protecting residents - this project will develop the technology and strategy to address that gap across OTI's programs including Cybersecurity, 311, and Digital Equity. TASKS: Develop quality code that is well-documented, testable, and production-ready Be proactive and seek feedback to ensure best practice solutions that meet business needs Building web solutions that are scalable and secure and align with overall city digital architecture Write and conduct unit testing as agreed with the City Engineering leads. Communicate technical decisions, needs, and priorities to engineers, product managers, and designers as part of a user-centered agile product delivery team Design the core logic with the existing vendor for the mobile application on iOS and Android to provide scam and spam protection for calls and texts. Build a responsive, accessible frontends resource sites that ensures a consistent experience across all browser types and mobile devices and leverages the NYC Design System. Apply rigorous industry-standard privacy and security standards and protocols to ensure that all user data remains private and secure. Develop the technical bridges necessary to route digital reporting data into existing intake and reporting systems. If necessary, learn new programming languages or frameworks, with help from City Engineering leads, to complete software development and testing tasks. Attend, participate, and assist in architecture, approach, and technical strategies as appropriate and requested by City Engineering leads. Mandatory Skills: At least 4 years of experience as a software engineer or application developer Experience building responsive websites with full-stack expertise Experience collaborating with product designers on cross-functional teams to ensure the best user experience. Experience working with Git based workflows Experience working in story-based workflows (e.g., Azure DevOps, JIRA, Trello, or other story or kanban-style workflow) Experience leading technical design and writing implementation planning documents Strong verbal and written communication skills Regards, Srikanth (Sri) Senior Recruiter Phone: Email: Powered by JazzHR I8bEmzW0Mq
Machine Learning Engineer 4 Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that streamline the auto financing process for dealers. Our team focuses on creating integrated, secure, and user friendly platforms that enhance dealer operations and customer experiences, ensuring compliance with the latest financial regulations. This pivotal role supports business growth and fosters strong dealer relationships, making every transaction smoother and more efficient. Dealer Tech within Financial Services Technology at Capital One is specifically designed to address the technological needs of auto dealers who partner with Capital One. This division focuses on developing and maintaining systems that facilitate the smooth operation of auto financing, from loan origination to funding. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/07/2026
Full time
Machine Learning Engineer 4 Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that streamline the auto financing process for dealers. Our team focuses on creating integrated, secure, and user friendly platforms that enhance dealer operations and customer experiences, ensuring compliance with the latest financial regulations. This pivotal role supports business growth and fosters strong dealer relationships, making every transaction smoother and more efficient. Dealer Tech within Financial Services Technology at Capital One is specifically designed to address the technological needs of auto dealers who partner with Capital One. This division focuses on developing and maintaining systems that facilitate the smooth operation of auto financing, from loan origination to funding. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
Full time
Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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).
10/02/2026
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 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
Full time
Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that streamline the auto financing process for dealers. Our team focuses on creating integrated, secure, and user friendly platforms that enhance dealer operations and customer experiences, ensuring compliance with the latest financial regulations. This pivotal role supports business growth and fosters strong dealer relationships, making every transaction smoother and more efficient. Dealer Tech within Financial Services Technology at Capital One is specifically designed to address the technological needs of auto dealers who partner with Capital One. This division focuses on developing and maintaining systems that facilitate the smooth operation of auto financing, from loan origination to funding. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
Full time
Machine Learning Engineer 4 Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that streamline the auto financing process for dealers. Our team focuses on creating integrated, secure, and user friendly platforms that enhance dealer operations and customer experiences, ensuring compliance with the latest financial regulations. This pivotal role supports business growth and fosters strong dealer relationships, making every transaction smoother and more efficient. Dealer Tech within Financial Services Technology at Capital One is specifically designed to address the technological needs of auto dealers who partner with Capital One. This division focuses on developing and maintaining systems that facilitate the smooth operation of auto financing, from loan origination to funding. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 (Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $179,400 - $204,700 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
Full time
Machine Learning Engineer 4 (Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $179,400 - $204,700 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
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. New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. 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. 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. Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
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. 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. 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. Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
Full time
Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/02/2026
Full time
Machine Learning Engineer 5 (Senior Manager, IC) In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 5 (Senior Manager, IC) 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).
10/02/2026
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).