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Senior System Integration & Test (I&T) Engineer Contract Position 12+ months 40 hours weekly, Hybrid role 3 days onsite 2 days WFH This position requires an Active DoD Secret Client is focused on delivering National Defense capabilities by driving mission-focused strategies to develop advanced technology systems enabling products and solutions focused on achieving the customer vision. Our programs deliver sustainable, reliable, and cost-efficient capabilities focused on end-customer needs that function in operationally relevant environments and timeframes. We consider the entire lifecycle of the solution, from conceptualization and architecting, through development to deployment, while leveraging novel technologies to deliver first-of-a-kind systems. We are seeking a Senior System Integration & Test (I&T) Engineer in our Woburn, MA office to support integration and test of advanced multi-function RF systems. The I&T Engineer should have experience performing subsystem and system level integration and test of software and/or hardware components to include building test sets and test software to verify system interfaces and functionality implementation against requirements. The I&T Engineer should have familiarity with automated test tools and techniques, writing and executing test plans and procedures, and contributing to system design packages. This position offers the opportunity to work with leading domain experts in sensors development, data analytics, and cyber security. The I&T Engineer will be expected to work closely with development teams to execute system testing both in a SIL environment as well as field tests. Experience with the Agile development process and associated tools is desired. This position is well suited for an engineer who has experience building DoD systems and is interested in hands on testing and fielding of novel systems developed by the client Both hardware and software-centric candidates are encouraged to apply to meet comprehensive system testing needs. Client is adopting Digital Engineering (DE) tools and techniques, including the integration of verification aspects of design as part of a comprehensive Model-Based Systems Engineering (MBSE) approach. Candidates will be expected to work with Systems Engineers to integrate I&T processes & artifacts into the DE workflow for programs, using MBSE tools to capture those aspects of the design related to verification, with traceability to external tools as required. What you will do: Working closely with domain experts, development teams, and systems engineers to design and develop hardware test sets and develop test software Hands on integration work in both hardware labs and field-test environments to ensure that software and hardware components are integrated into the system according to specification Experience in preparing and delivering briefings, familiarity with the execution of technical reviews (SRRs, PDRs, CDRs, TIMS, TRRs) Documenting and executing test plans and procedures Capturing and communicating test results and metrics This position requires an Active DoD Secret Clearance with the ability to obtain a Top Secret (TS) Security Clearance, for which U.S. citizenship is needed by the U.S. Government BS in Computer Science, Electrical Engineering, Systems Engineering, Aerospace Engineering, or related technical field with a minimum 5 years of relevant experience Proficiency in testing RF Systems Familiarity with containerized software Proficiency in Python, MATLAB, or Labview Familiarity with Ansible, Podman/Docker, Unit Test Frameworks, Artifactory Minimum of 3 years of experience working in I&T Travel required Nice to Have: Active Top Secret Security Clearance Domain expertise in one or more of the following areas is desirable; Radar, Electronic Warfare Antenna Apertures, Sensor Resource Management, Sea/Air/Space, Large-Scale Platform Test Systems, Cyber Physical Systems, Open System Architectures (UCI, OMS, COARPS) Proficiency in automated test tools and techniques Proficiency in bash scripting and Linux Operation Systems Familiarity with C/C++ Familiarity with MBSE tools such as Cameo (MagicDraw), Sparx Enterprise Architect, IBM Rational Rhapsody Familiarity with specific government open architectures (e.g., Open Mission Systems)

Sr Staff Embedded Systems Engineer, Wellness Work Mode: Onsite Location: Onsite 4 - Kohler, WI Opportunity Shape the future of at-home wellness-where water, hardware, firmware, and environment come together to restore, recover, and re-energize. As a Senior Staff Embedded Systems Engineer, you will turn emerging technologies into real, physical experiences - systems that can be felt, not just described. You will define architecture, build working solutions, and prove performance in the environments where it matters most. This is a role for a hands-on leader who creates momentum through action, bringing Kohler's vision for elevated daily rituals to life. Core Responsibilities Lead by doing. Define system requirements, design, build, test, and refine working hardware and firmware from first concept through validation, creating tangible wellness experiences that perform in the real world. Define system architecture. Architect robust, end-to-end embedded systems that unify electronics, firmware, sensing, and controls with water, steam, thermal, lighting, and air. Establish scalable platforms that enable consistent, elevated experiences across products. Engineer systems that are felt. Design and develop integrated hardware (PCBAs, control systems, sensor networks, and electro-mechanical interfaces) that deliver comfort, precision, and reliability in demanding bathroom environments. Own electronics execution. Lead schematic design, PCB layout, component strategy, and bring-up, driving hardware from concept into validated, production-ready systems. Design for real-world conditions. Create solutions that perform under heat, humidity, and water exposure, balancing durability, safety, and long-term reliability through strong engineering fundamentals. Integrate firmware with intent. Ensure responsive, intuitive control, translating hardware capability into seamless user experience. Prototype the experience. Build early and test often using hands-on iteration to validate not only function, but how the system restores, relaxes, and performs. Prove feasibility. Bring clarity to ambiguity, defining requirements, identifying risks, and validating solutions through structured testing, tolerance analysis, and costed execution plans. Drive manufacturability. Translate complex systems into scalable, buildable solutions aligned with supplier capability and production realities. Protect and create IP. Develop hardware innovations that are both differentiated and defensible, strengthening Kohler's leadership in wellness. Stay ahead. Continuously explore advancements in sensing, control, and environmental systems to inform what comes next. Communicate with clarity. Deliver focused, technically grounded insights that accelerate decisions and de-risk execution. What Success Looks Like Embedded systems that don't just function, but elevate daily ritual into meaningful wellness experiences Scalable platforms that bring consistency and differentiation across product lines First-to-market innovations that integrate seamlessly into real environments Patented technologies that define Kohler's leadership in wellness Skills/Requirements Bachelor's degree (or higher) in Electrical Engineering, Computer Engineering or equivalent 8-10+ years delivering consumer product NPD Hands-on builder with a strong sense of ownership and follow-through Deep expertise in embedded systems (electronics + firmware integration) including architecture and design of complex electromechanical products Strong mixed-signal analog and digital circuit design fundamentals Board-level design and validation of electronic circuits including component selection, schematic capture, and PCB layout (Altium preferred) Experience developing and leading implementation of test plans for hardware/firmware, and to ensure regulatory compliance (EMC, FCC, CE, UL, etc) Real-time embedded systems experience with microprocessors and microcontrollers Demonstrated experience in firmware design and documentation practices Strong knowledge in embedded C/C++ and object-oriented programming Demonstrated knowledge and experience in writing firmware for applications incorporating RTOS DfX and quality management methodologies (FMEA, DFMEA, DFM/DFA) Strong root cause analysis and debugging capabilities of both hardware and firmware Preferred Power electronics and power conversion Environmental sensing (temperature, humidity, flow, air) Connected systems (BLE, Wi-Fi, MQTT, Matter) Exposure to biometrics or machine learning CUSTOM.PAY.TRANSPARENCY Why Choose Kohler? We empower each associate to with a competitive total rewards package to support your health and wellbeing, access to career growth and development opportunities, a diverse and inclusive workplace, and a strong culture of innovation. With more than 30,000 bold leaders across the globe, we're driving meaningful change in our mission to help people live gracious, healthy, and sustainable lives. About Us It is Kohler's policy to recruit, hire, and promote qualified applicants without regard to race, creed, religion, age, sex, sexual orientation, gender identity or expression, marital status, national origin, disability or status as a protected veteran. If, as an individual with a disability, you need reasonable accommodation during the recruitment process, please contact . Kohler Co. is an equal opportunity/affirmative action employer.

Job Description Job Description Description: POSITION SUMMARY: Works under minimum supervision to maintain Victory Channel traffic and content management systems. PRINCIPAL DUTIES AND RESPONSIBILITIES: Daily Duties Create the Daily Traffic Log (Playlist) in BroadView and deliver to Master Control Daily Reconcile Playlist and AsRun in BroadView Review Daily Vimeo Upload Status Report and collect all outstanding media Daily Comscore Reporting - generate and upload to Comscore FTP Weekly Responsibilities Create Program Guide and send to various outlets (Dish, DirecTV, etc.) Generate, format & send weekly program guide for Victory Updates Maintain Spots & Features Showcase in Vimeo Maintain electronic program guide for Victory Channel website, OTT, and mobile apps through Media Control and WordPress Download program files for programmers who deliver in non-standard way Monthly Duties Generate Offering Log (BVOV and Support spots), send to Accounting Generate and send Expired Traffic Items Report to Master Control Maintain lists of active and archived interstitial in Broadview. Generate and upload monthly on-air logs to Palatka station Upload applicable interstitial for Palatka to air, Notify Master Control when complete Annual or Semi-Annual Responsibilities Notify Production Scheduler of Seasonal Interstitial aired in the past Report Holidays Observed with :10 Station ID Create new annual BroadView Scheduling Series' with Media, Categories, House Numbers Rebuild Scheduler according to current Broadcast Schedule As Needed/Intermittent Duties Coordinate with Broadcast Operations Manager on approvals to air interstitial Assign appropriate airtime rights to interstitial and apply rotation instructions using BroadView software as per policy and/or as directed by Broadcast Operations Manager Assign appropriate IDs and transfer interstitial to Master Control on a timely basis Coordinate with spot producers about scheduling spots/promos that will air on the network Communicate with spot producers when delivered spots have failed QC Manually QC files that fail automated QC check to verify whether reported file issues are accurate, notify Programmer Liaison Notify Master Control about scheduling changes/pre-tapes for live programs Set up KCM meetings/FlashPoint live events in BroadView, determine which events will air on the network as directed by Broadcast Operations Manager Work with Broadcast Operations Manager on special weeks on VICTORY like Victorython, Southwest Believers Convention, and Victory Week Send final schedules for special weeks to appropriate parties internally through Programmer Liaison Request and upload thumbnails for ministry-related special events and meetings on Victory Channel website/OTT/and show pages Send special program graphics to Zype team who updates to mobile app program guide Send EMIC quarterly service estimate to Accounting/distribution Keep track of status of new programmers and communicate updates to Broadcast Operations Manager and Marketing/Communications Create Program ID for new programmers and set up FTP access, send password to single contact Create new scheduling series in Broadview with media for new programmer Collect new and/or revised programmer show graphics, distribute to Zype team for updates, upload appropriate thumbnails to media control and Wordpress, distribute to Gracenote and others on distribution list Change thumbnails in Media Control as appropriate for LIVE events Answer questions/requests about network schedule or what has aired Report program preemptions to Programmer Liaison, notify impacted programmers Assist Network Manager with proposed schedule changes Generate individual programmer airtime documents and provide to Programmer Liaison to communicate schedule changes to programmers Provide Programmer Liaison revised Victory schedules for distribution to KCM departments Work regular schedule rotation for Viewership Statistics reporting of live programs Maintain Roku and menus with current correct programming including specials Support tech in researching and documenting absolutely all digital content created and produced by the ministry, where it is distributed, and who is the contact for sending/posting. Other duties as assigned/requested. Requirements: JOB REQUIREMENTS Education: Associates Degree in Communications or Business preferred Experience in or ability to learn BroadView traffic management software Experience in writing business or technical manuals Experience: Experience in broadcast television preferred Knowledge/Skills/Abilities: Extremely organized and highly disciplined, with the ability to prioritize tasks and anticipate needs. Must be able to multi-task. Ability to perform in a team environment Ability to communicate effectively verbally and in writing Ability to interpret and follow technical plans Ability to quickly learn and put to use new skills and knowledge brought about by rapidly changing information and/or technology Able to prioritize and set goals Able to meet deadlines, and deliver projects on time Able to resolve problems, handle conflict and make effective decisions Must relate and interact with people at all levels Exceptional written and verbal communication skills Type 55 WPM with minimum errors Ability to adapt and respond to constantly changing priorities. A wide degree of self-initiative, creativity and latitude is expected. EQUIPMENT TO BE USED Standard office equipment TYPICAL PHYSICAL DEMANDS Must be able to sit at a computer for 5-7 hours per day Requires manual dexterity sufficient to operate standard office machines such as computers, fax machines, calculators, telephones and other office equipment Requires normal range of hearing and vision TYPICAL MENTAL DEMANDS Ability to give, receive and analyze information, formulate work plans, prepare written materials and articulate goals and action plans. Must be very organized and require a limited amount of instruction. Must be very detailed, organized, and communicative. Must be task and goal oriented. Requires the ability to multi-task Must adapt well to changing work situations. Must be able to grasp and apply new ideas. Must be able to resolve problems, handle conflict and make effective decisions. Must relate and interact with people at all levels. WORKING CONDITIONS Typical office environment Other: Born again believer and must adhere to the doctrines of this organization as upheld by Kenneth and Gloria Copeland and their appointed representatives Must work well with others, as a team and according to Romans 16:17, must not cause dissension, difficulties and divisions Must maintain a good attendance record Membership and attendance at EMIC are preferred Because of the wide range of personal contact with ministry leaders within and outside the organization, this position requires considerable diplomacy, maturity, and excellent communication skills Ability to work with people of all cultures DISCLAIMER This job description is not intended and should not be construed to be an exhaustive list of all responsibilities, skills, efforts and working conditions associated with this position. It does however reflect the principal job element of this position. This job description does not constitute a contract for employment.

Job Description Job Description Hello, "Join GD Resources for dynamic opportunities in business management and IT, where innovation meets excellence." About the Company: GD Resources is a Veteran Women-Owned Business Management and Information Technology company committed to excellence. GD Resources provides dynamic opportunities for veterans and professionals alike to contribute to innovative projects and drive success in a collaborative and supportive environment. Join us to make a difference, advance your career, and grow with a company that values integrity, diversity, and continuous improvement. Experience8-12 YearsClientNew York City - DoITTDuration6 MonthsPrimary SkillsIOS, Android, JIRA, azure, Product Manager, Trello, DevOpLocation Brooklyn, NY, 11201 Job Start Date2026-05-04Remote JobNoRequired Hours/Week35Job TypeContract Public Job TitleMid Level - Mobile App Developer (iOS & Android)Public Job DescriptionNYC Office of Technology and Innovation Job Title: Mid Level - Mobile App Developer (iOS & Android) Duration: 6+ Months with possible extension Location: 15 Metrotech Center, Brooklyn, NY 11201 Position Type: Contract Interview Type: Webcam/In-person Note: Normal Business Hours, Monday through Friday (not including a mandatory unpaid meal break after 6 hours of work), 35 work hours per week. If the consultant works more than 35 hours per week, the consultant must request overtime in the Agency's timekeeping system, and the project manager must approve those hours worked above the weekly maximum. SCOPE OF SERVICES: The developer will be responsible for overseeing the end-to-end technical execution of the new features in the NYC Secure App on iOS and Android and development of other digital resources as needed. The developer will deliver a scalable, privacy-centric systems that integrates with existing NYC data services, workflows, and web platforms. Job Description: The NYC Office of Technology and Innovation has been tasked with re-designing the NYC Secure App and an associated campaign to provide New Yorkers with a comprehensive set of tools and resources to prevent scam phone calls and text messages, educate vulnerable New Yorkers on prevention, and support New Yorkers with the resources they need when they have been victimized. Each year New Yorkers lose an estimated $6.5B to online and phone based scams, yet the city provides no systematic approach to protecting residents - this project will develop the technology and strategy to address that gap across OTI's programs including Cybersecurity, 311, and Digital Equity. TASKS: Develop quality code that is well-documented, testable, and production-ready Be proactive and seek feedback to ensure best practice solutions that meet business needs Building web solutions that are scalable and secure and align with overall city digital architecture Write and conduct unit testing as agreed with the City Engineering leads. Communicate technical decisions, needs, and priorities to engineers, product managers, and designers as part of a user-centered agile product delivery team Design the core logic with the existing vendor for the mobile application on iOS and Android to provide scam and spam protection for calls and texts. Build a responsive, accessible frontends resource sites that ensures a consistent experience across all browser types and mobile devices and leverages the NYC Design System. Apply rigorous industry-standard privacy and security standards and protocols to ensure that all user data remains private and secure. Develop the technical bridges necessary to route digital reporting data into existing intake and reporting systems. If necessary, learn new programming languages or frameworks, with help from City Engineering leads, to complete software development and testing tasks. Attend, participate, and assist in architecture, approach, and technical strategies as appropriate and requested by City Engineering leads. Mandatory Skills: At least 4 years of experience as a software engineer or application developer Experience building responsive websites with full-stack expertise Experience collaborating with product designers on cross-functional teams to ensure the best user experience. Experience working with Git based workflows Experience working in story-based workflows (e.g., Azure DevOps, JIRA, Trello, or other story or kanban-style workflow) Experience leading technical design and writing implementation planning documents Strong verbal and written communication skills Regards, Srikanth (Sri) Senior Recruiter Phone: Email: Powered by JazzHR I8bEmzW0Mq

Job Description Job Description Mission Context LV8D Solutions supports national security space and intelligence customers delivering next-generation sensing and exploitation capabilities. The role of a Security Control Assessor (SCA) is focused on providing information security Assessment and Authorization (A&A) support throughout the mission program's lifecycle. Position Overview LV8D Solutions is seeking a SCA to conduct independent assessments of the management, operational, and technical security controls employed within or inherited by an information technology (IT) system to determine the overall effectiveness of the security controls. A Security Control Assessor (SCA) performs comprehensive INFOSEC assessment of management, operational, and technical security controls to determine overall effectiveness of the controls for A&A determination throughout a program's system lifecycle. SCAs provide an assessment of the severity of weakness or deficiencies discovered in the Information System (IS) and its environment of operation and recommend corrective actions to address identified vulnerabilities. Prior to initiating the security control assessment, the SCA reviews the System Security Plan (SSP) to ensure the plan provides a set of security controls for the ISs that meet the stated security requirements. Additionally, the SCA must verify that all allocated controls have an acceptable status (i.e., implemented, excepted, or inherited) with appropriate documented details and provides responses in the Government's Risk Management Framework (RMF) tools. Interested candidates need to thrive in an innovative, fast-paced environment; are highly motivated and not afraid to take on uncharted territory; possess strong communication, leadership, and organizational skills; and be able to prioritize their time to be effective in a dynamic environment. Requirements Key Responsibilities Reviews IS for compliance with applicable Intelligence Community (IC), Department of War (DoW), and National Directorate (ND) guidance, and make recommendations to the Government. Provides ISs security advice and guidance Joint Analytical Workstation (JAW) applicable IC, DoW, and NDs and guidance to Government and industry partners for the protection of data at all classification levels including Sensitive Compartmented Information (SCI). Evaluates threats and vulnerabilities to ISs to ascertain the need for additional safeguards and recommend approval, disapproval, or waiver(s) for IS processing national security data at industry and/or Government facilities. Supports development and implementation of directives and guidance for policies. Provides input for consideration in the promulgation of future ISs security policy. Supports and/or conduct site visits and assessments to inspect and verify IS reports. Ensures security control assessments are completed for each IS. Supports the preparation and delivery of presentations, briefings, reports, and memoranda associated with the RMF process. Uses the RMF system of record to complete RMF workflow duties and maintain the asset documentation repository. Establishes and maintains means and methods to track RMF process workflow activities to inform task volume, velocity, and duration of activities. Prepares the final Security Assessment Report (SAR) containing the results and findings from the assessment at the conclusion of each security control assessment activity and the Authorization Recommendation. Ensures appropriate IS security requirements including applicable Interface Control Documents (ICDs), DoW Instructions, NDs and other guidance are addressed and applied and appropriate documentation is prepared by the system owners or programs. The documentation will be contained in the Security Assessment Package, including, but not limited to, the Concept of Operations (CONOP), SSP, Systems Requirements Traceability Matrix, Risk Management Matrix, Test Results, interface control documents, requests for changes, test plans, and other related program security documentation. Collaborates with Information Security Officers (ISOs) and Common Control Providers to initiate Plan of Action and Milestones (POAMs) for ISs based on findings and recommendations from the SAR. Reviews and approves the IS Security Assessment Plan which is comprised of the Security Controls Traceability Matrix and the Security Control Assessment Procedures. Tracks the completion of the SAR. Reviews, coordinates, and responds to security issues as requested by the Government. Provides A&A support to the Government for the protection of special programs and tactical operations related activities. Supplies the effort needed to conduct the reviews and write reports to support Integrated Security Assessment Program (ISAP) or Technical Information Systems Security Reviews (TISSRs). Required Qualifications Practical experience performing information systems A&A as defined in applicable ICDs and guidance Practical experience utilizing risk management strategies for information technology solutions Technical understanding of emerging technologies and their implementation within Government system and network environments Knowledge of information technology concepts used in the evaluation of security performance and integrity of state-of-the-art applications, communications systems, hardware, software, satellite control systems, and information processing systems Technical understanding of information technology systems, software, and networks Ability to effectively coordinate A&A activities of industry and Government information systems to meet acquisition milestone requirements Effective technical report and general correspondence writing ability Ability to manage and track systems or programs involved in the A&A process Experience developing and implementing security related directives and guidance for Information Assurance, Information Technology, and Information Management Experience working with a mixed level skill team to ensure that appropriate knowledge and skill transfer occurs High school's degree and 7+ years of relevant experience, or Associate's degree and 7+ years of relevant experience, or Bachelor's degree and 5+ years of relevant experience, or Master's degree and 3+ years of relevant experience Certifications Must have one of the following IAM Level 2 Certification: CGRC (Previously CAP) CASP CISM CISSP GSLC CCISO Security Requirements U.S. Citizenship Active Top Secret/Sensitive Compartmented Information (TS/SCI) clearance Active Counterintelligence (CI) or Full Scope (FS) Polygraph Work Environment On-site work in a government or contractor facility Occasional travel (up to 10%) This position is dependent on a contract seat being awarded. About LV8D Solutions LV8D Solutions is an elite Systems Engineering and Technical Advisory (SETA) company that delivers advanced systems engineering, integration, acquisition, mission operations, network communications, and cybersecurity support to our defense and intelligence customers. Founded in 2019, we apply our deep technical expertise, understanding, and mission-first mindset to design, acquire, and implement complex, high-impact solutions for our Intelligence Community (IC) and Department of War (DoW) customers. We specialize in every aspect of our customers' space and ground mission systems while offering exceptional work-life balance and an exemplary compensation and total rewards package designed to recruit, train, and retain top talent and committed to national defense and career growth. Equal Employment Opportunity Statement LV8D Solutions LLC is an Equal Opportunity Employer committed to diversity and inclusion. All qualified applicants will receive consideration without regard to race, religion, gender, national origin, disability, veteran status, or other protected categories. Benefits Performance & Recognition Period of Performance (PoP) Bonus Opportunities Performance-based bonus opportunities tied to contract or organizational performance. Retention Incentive Benefit Bounty Receive a payout for unused annual company contributions designated for health insurance premiums and professional training. Referral Bonus Earn up to $5,000 for each successful employee referral. Customer Recognition Letter of Appreciation (LoA) Bonus Opportunities Bonus opportunities based on customer recognition received through Letters of Appreciation. Milestone Rewards Celebrate your career achievements with anniversary awards on your 1st, 5th, 10th, and 20th years of service. Financial & Retirement Benefits Profit Sharing Receive an annual contribution equal to 4% of your W-2 gross earnings into your 401 (k), with immediate vesting. 401(k) Company Match The company matches your 401 (k) contributions dollar-for-dollar up to 6% of your monthly contribution, with immediate vesting. Career Development The company invests in your professional growth through: Annual financial support for professional training and industry certifications. Enhanced financial support for employees actively pursuing a degree at an accredited institution. Work-Life Balance . click apply for full job details

Job Description Job Description About Us AGE Solutions is a premier technology and professional services company, providing in-depth consulting, advanced technology solutions, and essential services throughout the U.S. government, defense, and intelligence sectors. Prioritizing innovation and client-focused solutions, we assist major agencies in addressing intricate issues and ensuring a more secure future. AGE Solutions is looking for a Cloud SCA-R, Senior to join our team in support of an upcoming cybersecurity risk management and assessment program with our DoD customer. As a Team Lead, you will be responsible for performing analysis, conducting independent validations of assessments, and Continuous Monitoring (ConMon) for authorized CSPs and CSOs. Individuals in this role must be available to work full-time on-site at Ft. Meade, MD. Duties and Responsibilities Include: Conduct cybersecurity assessments and validations of Cloud Service Offerings (CSOs) in support of the Department of Defense (DoD) Provisional Authorization (PA) process. Evaluate Cloud Service Provider (CSP) documentation packages following government guidance and procedures, including key artifacts such as the Cloud Architecture Diagram, System Security Plan (SSP), SSP Addendum, Readiness Assessment Report (RAR), System Architecture, Security Assessment Plan (SAP), Security Assessment Report (SAR), and associated Plans of Action & Milestones (POA&Ms). Review, analyze, and process additional documents including Change Requests, Extension Requests, Deviation Requests, Whitelist Requests, Corrective Action Plans, templates, process guide approvals, and continuous monitoring (ConMon) artifacts for existing Provisional Authorizations. Prepare and deliver up to 30 Cloud Security Assessment Packages annually, each including validated cybersecurity controls, certifier recommendations, and a statement of residual risk. Participate in technical kickoff meetings and review preliminary documentation to assess a CSP's readiness posture. Analyze and provide detailed feedback on CSP submissions such as the RAR, SAP, SSP, and architectural diagrams. Assess and document the operational impact of authorizations, changes, and vulnerabilities on the CSP environment. Develop Cloud Security Assessment Packages in accordance with established guidelines, including the SAR, POA&M, and any Deviation Requests. Draft Authorization Recommendation Memoranda outlining CSO compliance with DoD cybersecurity controls, residual risks, and technical findings. Prepare formal DoD Provisional Authorization memoranda, detailing authorization length, CSO boundary, services provided, operating conditions, DoD usage considerations, and follow-on activities. Validate CSO controls within eMASS or other government-provided Governance, Risk, and Compliance (GRC) tools; ensure accurate tracking in the Mission Status Report (MSR). Review and verify the Customer Responsibility Matrix (CRM), ensuring proper control inheritance is reflected in eMASS/GRC systems. Upload authorization conditions as system-level POA&Ms in eMASS and monitor their resolution. Organize and associate all received documentation with applicable security controls within eMASS. Maintain and update the DoD Cloud Process Guide, including all checklists, templates, forms, and guidance documents. Assist in developing internal requirements and how-to guides for assessors conducting CSP validations. Document and refine assessment procedures and validation best practices to align with DoDI 8510.01 and the DoD Cloud Computing Security Requirements Guide (SRG). Contribute to the ongoing development and annual updates of the DoD Cloud Assessment Process Guides as requested by the Government. Requirements: Bachelor's degree (IT-related field preferred) Eight (8) years of overall experience in cybersecurity or network security position Have an active DoD Top Secret clearance with SCI eligibility DoD 8570 IAM/IA Technical (IAT) Level III certification Familiarity with security controls for Azure, AWS, and assorted cloud platforms Solid understanding of DoD Risk Management Framework (RMF), DoDI 8510.01, and DoD Cloud Computing Security Requirements Guide (SRG) Familiarity with security controls for Azure, AWS, and assorted cloud platforms Hands-on experience with eMASS or other government-provided GRC tools Familiarity with cloud security documentation, including SSPs, SARs, RARs, and POA&Ms Ability to analyze complex cloud architectures and provide accurate risk assessments Strong technical writing and communication skills to produce security assessment reports and formal recommendations Applicants must reside within a commutable distance of Ft. Meade, MD in order to work onsite full time. The projected salary range for this position is $115,000+ annually. Final compensation will be determined based on factors including years of relevant experience, active security clearance level, certifications, technical skillset, contract requirements, and overall qualifications. At AGE Solutions, we reward performance, invest in growth, and share success. Our benefits support the whole person, professionally, financially, and personally. 26 Days Paid Leave: Includes vacation, sick, personal time, and holidays. You choose how to use it. Performance Bonuses: Performance bonuses are awarded based on individual contributions and company-wide results, aligning recognition with impact. 401(k) with Match: We match 3% of your contributions with immediate vesting. Financial Protection: Company-paid life insurance up to $300K and options for additional coverage for you and your dependents. Health Benefits: Multiple medical plans, dental, vision, FSA and HSA options to fit your needs. Parental Leave: 15 days of fully paid leave for new parents, because family matters. Military Differential Pay: We bridge the gap for employees on active duty, so they don't take a financial hit while serving. Professional Growth: Paid training and certifications, tuition reimbursement, and the tools and tech to get the job done right. Shared Success: In the event of a company sale, our CEO has committed to returning 80% of net proceeds to employees. This ensures our team shares in the long term value they help create. At AGE, you'll do work that matters, supported by a company that delivers for its people.

Job Description Job Description About Us AGE Solutions is a premier technology and professional services company, providing in-depth consulting, advanced technology solutions, and essential services throughout the U.S. government, defense, and intelligence sectors. Prioritizing innovation and client-focused solutions, we assist major agencies in addressing intricate issues and ensuring a more secure future. AGE Solutions is looking for a Cloud SCA-R, Mid, to join our team in support of a cybersecurity risk management and assessment program with our DoD customer. In this role, you will be part of a team responsible for performing analysis, conducting independent validations of assessments, and Continuous Monitoring (ConMon) for authorized CSPs and CSOs. Individuals in this role must be available to work full-time on-site at Ft. Meade, MD. Essential Duties and Responsibilities Include: Conduct cybersecurity assessments and validations of Cloud Service Offerings (CSOs) in support of the DoD Provisional Authorization (PA) process Prepare 30 Cloud Security Assessment Packages per year, including validated cybersecurity controls, certifier's recommendations, and residual risk statements Review Cloud Service Provider (CSP) documentation packages, including architectural diagrams, System Security Plans (SSP) with Addendums, Readiness Assessment Reports (RAR), Security Assessment Plans (SAP), and Security Assessment Reports (SAR) Evaluate supporting materials such as POA&Ms, Change Requests, Extension and Deviation Requests, Whitelist Requests, Corrective Action Plans, and applicable templates, checklists, and Continuous Monitoring (ConMon) artifacts Attend technical kickoff meetings to evaluate and document the CSP's security posture and readiness for assessment Analyze and provide feedback on assessment documentation, including the RAR, SAP, SSP, and system architecture diagrams Identify and document the operational impact of security authorizations, changes, or identified vulnerabilities within the CSP's environment Develop complete Cloud Security Assessment Packages in accordance with DoD standards, ensuring inclusion of SARs, POA&Ms, and Deviation Requests Create authorization recommendation memorandums summarizing compliance with DoD cybersecurity controls, technical evaluation results, and residual risk considerations Draft DoD PA memorandums outlining CSO boundary definitions, service offerings, authorization duration, terms and conditions, DoD usage considerations, and follow-on actions Validate implementation of CSO controls within eMASS or a government-provided GRC platform, and log assessment completion in the Mission Security Review (MSR) Review the Customer Responsibility Matrix (CRM) and ensure correct inheritance mapping within eMASS or the designated GRC tool Enter all authorization conditions into eMASS as system-level POA&Ms and monitor for timely resolution Upload and associate all CSP documentation with applicable security controls in eMASS or the appropriate system of record Track and manage all CSO-related data using the Team Lead Resource (TLR) Assessment Database Maintain and update the DoD Cloud Process Guide and associated templates, forms, checklists, and documentation Contribute to the development of internal instructions, how-to guides, and reference material to support consistent assessor workflows Ensure assessment activities are conducted in compliance with DoDI 8510.01 and the DoD Cloud Computing Security Requirements Guide (SRG) Document assessment methodologies and validation best practices to continuously improve assessment accuracy, consistency, and process efficiency Support the ongoing development and annual updates of the DoD Cloud Assessment Process Guides in alignment with evolving policy and government directives Required Qualifications: Education: Bachelor's degree (IT-related field preferred) Experience: Five (5) years of overall experience in cybersecurity or network security position Security Clearance: Must have an active DoD Top Secret clearance with SCI eligibility Certifications: DoD 8570 IAM/IA Technical (IAT) Level II certification Skills and Knowledge: Working knowledge of DoD Risk Management Framework (RMF) and DoDI 8510.01 Familiarity with the DoD Cloud Computing Security Requirements Guide (SRG) and associated cloud security policies Familiarity with security controls for Azure, AWS, and assorted cloud platforms Experience conducting security assessments and developing security documentation (e.g., SSP, SAR, POA&M, SAP) Proficiency with eMASS or equivalent Government Risk and Compliance (GRC) tools Demonstrated ability to interpret and apply NIST SP 800-53 security controls in cloud environments Strong analytical and technical writing skills with the ability to communicate complex topics clearly Location: Applicants must reside within a commutable distance of Ft. Meade, MD in order to work onsite full time. The projected salary range for this position is $100,000+ annually. Final compensation will be determined based on factors including years of relevant experience, active security clearance level, certifications, technical skillset, contract requirements, and overall qualifications. At AGE Solutions, we reward performance, invest in growth, and share success. Our benefits support the whole person, professionally, financially, and personally. 26 Days Paid Leave: Includes vacation, sick, personal time, and holidays. You choose how to use it. Performance Bonuses: Performance bonuses are awarded based on individual contributions and company-wide results, aligning recognition with impact. 401(k) with Match: We match 3% of your contributions with immediate vesting. Financial Protection: Company-paid life insurance up to $300K and options for additional coverage for you and your dependents. Health Benefits: Multiple medical plans, dental, vision, FSA and HSA options to fit your needs. Parental Leave: 15 days of fully paid leave for new parents, because family matters. Military Differential Pay: We bridge the gap for employees on active duty, so they don't take a financial hit while serving. Professional Growth: Paid training and certifications, tuition reimbursement, and the tools and tech to get the job done right. Shared Success: In the event of a company sale, our CEO has committed to returning 80% of net proceeds to employees. This ensures our team shares in the long term value they help create. At AGE, you'll do work that matters, supported by a company that delivers for its people.

Job Description Job Description Senior Cloud SCA-R Full Time 100% Onsite - Fort Meade, MD TOP SECRET Clearance AWS/AZURE We are seeking a Senior Cloud SCA-R to join our team in support of an upcoming cybersecurity risk management and assessment program with our DoD customer. As a Team Lead, you will be responsible for performing analysis, conducting independent validations of assessments, and Continuous Monitoring (ConMon) for authorized CSPs and CSOs. Must have and maintain an active DoD Top Secret clearance with SCI eligibility Responsibilities Include: Conduct cybersecurity assessments and validations of Cloud Service Offerings (CSOs) in support of the Department of Defense (DoD) Provisional Authorization (PA) process. Evaluate Cloud Service Provider (CSP) documentation packages following government guidance and procedures, including key artifacts such as the Cloud Architecture Diagram, System Security Plan (SSP), SSP Addendum, Readiness Assessment Report (RAR), System Architecture, Security Assessment Plan (SAP), Security Assessment Report (SAR), and associated Plans of Action & Milestones (POA&Ms). Review, analyze, and process additional documents including Change Requests, Extension Requests, Deviation Requests, Whitelist Requests, Corrective Action Plans, templates, process guide approvals, and continuous monitoring (ConMon) artifacts for existing Provisional Authorizations. Prepare and deliver up to 30 Cloud Security Assessment Packages annually, each including validated cybersecurity controls, certifier recommendations, and a statement of residual risk. Participate in technical kickoff meetings and review preliminary documentation to assess a CSP's readiness posture. Analyze and provide detailed feedback on CSP submissions such as the RAR, SAP, SSP, and architectural diagrams. Assess and document the operational impact of authorizations, changes, and vulnerabilities on the CSP environment. Develop Cloud Security Assessment Packages in accordance with established guidelines, including the SAR, POA&M, and any Deviation Requests. Draft Authorization Recommendation Memoranda outlining CSO compliance with DoD cybersecurity controls, residual risks, and technical findings. Prepare formal DoD Provisional Authorization memoranda, detailing authorization length, CSO boundary, services provided, operating conditions, DoD usage considerations, and follow-on activities. Validate CSO controls within eMASS or other government-provided Governance, Risk, and Compliance (GRC) tools; ensure accurate tracking in the Mission Status Report (MSR). Review and verify the Customer Responsibility Matrix (CRM), ensuring proper control inheritance is reflected in eMASS/GRC systems. Upload authorization conditions as system-level POA&Ms in eMASS and monitor their resolution. Organize and associate all received documentation with applicable security controls within eMASS. Maintain and update the DoD Cloud Process Guide, including all checklists, templates, forms, and guidance documents. Assist in developing internal requirements and how-to guides for assessors conducting CSP validations. Document and refine assessment procedures and validation best practices to align with DoDI and the DoD Cloud Computing Security Requirements Guide (SRG). Contribute to the ongoing development and annual updates of the DoD Cloud Assessment Process Guides as requested by the Government. Required Skills, Qualifications, and Experience: Education and Certifications: o Bachelor's degree (IT-related field preferred) o DoD 8570 IAM/IA Technical (IAT) Level III certification Experience: o Eight (8) years of overall experience in cybersecurity or network security position Skills and Knowledge: o Familiarity with security controls for Azure, AWS, and assorted cloud platforms o Solid understanding of DoD Risk Management Framework (RMF), DoDI, and DoD Cloud Computing Security Requirements Guide (SRG) o Familiarity with security controls for Azure, AWS, and assorted cloud platforms o Hands-on experience with eMASS or other government-provided GRC tools o Familiarity with cloud security documentation, including SSPs, SARs, RARs, and POA&Ms o Ability to analyze complex cloud architectures and provide accurate risk assessments o Strong technical writing and communication skills to produce security assessment reports and formal recommendations

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 7,000 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. Quality Control Tech shall have a strong knowledge of all inspection procedures and utilization of required measuring devices that correspond to the tasking in which they are assigned. Perform shipboard/alteration inspections referencing MIL-STD's, NAVSEA Standard Items, and MIL-SPEC's. Provide detailed reports documenting all "As Found" conditions during inspection, including Quality Assurance Workbook. Verify proper documentation of all required repairs and communicate identified deficiencies to production to initiate corrective actions. Ensure that all test and inspection documentation is accounted for and thoroughly completed prior to certification. Must have the ability to read and interpret blueprints, sketches, written technical instructions and manuals to develop Test and Inspection QA Workbooks, incorporating V, I, and G level inspection points to Test and Inspection Plans (TIP). Certification ISO Lead Auditor Training a plus Certified Quality Inspector Certification NAVSEA Connector Certification NAVSEA Cableway Certification NAVSEA Fiber Optic QA/Supervisor Training Structural fit-up, welding, pipefitting, and NDT Level II experience/qualification is a plus. Active OSHA 7615 Maritime Training 10hr Card Shipyard Competent Person Responsibilities Specific duties and responsibilities: Work directly with QAM, and Project Manager(s) to ensure all inspections requirements are properly identified in the Quality Assurance Workbook. Thorough knowledge of NAVSEA Standard Items, NAVSEA Technical Specification 9090-310, MIL-STDs and MIL-SPECs to objectively review on board installations and associated Objective Quality Evidence. Responsible to ensure that the quality of the product or services provided to the customer through the performance and documentation of all required inspections is in accordance with corresponding contractual requirements and company procedures. Review and certify all data, ensuring that performance and quality of products conform to establish company, international (ISO), and governmental regulatory standards and agency guidelines, and to ensure lasting customer satisfaction. Candidate must possess C5ISR Installation, Quality Assurance, or Quality Control experience. Approve finished products by confirming specifications; conducting visual and measurement tests; returning products for re-work; confirming re-work. Ensure that all QA forms, Test documents and any other form of Objective Quality Evidence (OQE) requiring initials, signatures or any other verifiable form or acknowledgement of completion are done in accordance with all applicable requirements. Maintain safe and healthy work environment by following standards and procedures, complying with legal regulations. Candidates must be able to physically access all areas on board U.S. Naval Vessels to include tanks, voids, and working aloft in support of production operations. Qualifications Other Required Skills Active secret security clearance desirable Clearance: Applicants selected will be subject to a government security investigation and may meet eligibility requirements, including U.S. Citizenship, for access to classified information; ability to obtain a Secret clearance is required. High school diploma with 6+ years of experience. Candidate must be able/willing to travel in CONUS/OCONUS ISO Lead Auditor Training a plus Fiber Optic Connector QA/Build training Must be able to successfully pass a criminal background check and obtain and maintain a security badge for all military installations and civilian shipyards. Must have or be able to obtain a passport 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.

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).

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).

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).

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).

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).