Capital One

Machine Learning Engineer

• Deliver ML models and software components solving business problems in financial services
• Collaborate with Product, Architecture, Engineering, and Data Science teams
• Drive the creation and evolution of ML models and software for intelligent systems
• Lead large-scale ML initiatives with the customer in mind
• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
• Optimize data pipelines feeding ML models
• Use Python, Scala, Java, and GoLang
• Leverage Dask and RAPIDS compute technologies
• Evangelize engineering and modeling lifecycle best practices
• Help recruit, nurture, and retain engineering talent

Staff Machine Learning Engineer

Risk

• Apply cyber best practices to assess current state, identify gaps, and assess cyber risk, threats, and business impact
• Define mitigation strategies and prioritize and escalate recommendations
• Participate in the design and implementation of cyber control programs
• Manage end-to-end controls lifecycle management and ensure adherence to the Enterprise Control Standard
• Oversee comprehensive design assessments for new controls
• Lead risk professionals as they help lines of business create and update controls
• Assess the impact of control changes on regulatory gap assessments, processes, and risks
• Build and monitor data-quality metrics for control data in the system of record
• Partner with Enterprise Services Risk Analytics to implement automated solutions for proactive risk management
• Support content development for Internal Audit and regulatory agencies
• Drive project and program delivery, reporting, facilitation of senior leadership meetings, and preparation of materials for senior management and the Board of Directors

Senior Manager, Tech Risk & Analysis

• Deliver ML models and software components solving challenging business problems in the financial services industry
• Collaborate with Product, Architecture, Engineering, and Data Science teams
• Drive creation and evolution of ML models and software enabling state-of-the-art intelligent systems
• Lead large-scale ML initiatives with the customer in mind
• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
• Optimize data pipelines to feed ML models
• Use programming languages such as Python, Scala, Java, and GoLang
• Leverage compute technologies such as Dask and RAPIDS
• Evangelize best practices across engineering and modeling lifecycles
• Help recruit, nurture, and retain top engineering talent

Senior Staff Machine Learning Engineer

Director

• Lead client and participant readiness initiatives
• Build and manage a dedicated participant enablement function
• Design an end-to-end readiness system
• Own the CRM ecosystem and marketing tool stack
• Define and execute the Salesforce and related enablement-platform roadmap
• Establish a single source of truth for participant metrics, referral tracking, and client performance analytics
• Oversee adoption, integration, and governance of marketing and enablement technologies
• Prioritize automation to reduce administrative friction while maintaining data accuracy
• Lead implementation and daily operation of merchant referral software, including RAM and RMS, within Salesforce
• Establish one system of record for merchant acceptance complaints
• Design referral workflows for seamless participant experience, accurate attribution, and automated dashboard distribution
• Develop CRM dashboards and KPI frameworks to monitor client programs, enablement initiatives, and referral performance
• Translate opportunities, engagement data, and referral metrics into actionable recommendations to improve participant engagement and conversion rates

Director of Participant Enablement

Full-stack Engineer

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems
• Share knowledge of technology trends, experiment with and learn new technologies, participate in internal and external technology communities, and mentor engineering community members
• Collaborate with digital product managers to deliver robust cloud-based solutions supporting millions of Americans’ financial empowerment
• Use Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, open-source RDBMS and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership and direction across Agile teams, setting standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify improvement opportunities, perform targeted refactoring, reduce technical debt, and enhance system performance
• Influence long-term technology strategy by evaluating emerging tools and practices in a “you build it, you own it” environment

Full-stack Engineer 4 – Enterprise Platform, Marketing Technology

• Lead a portfolio of diverse technology projects and a team of developers with experience in distributed microservices and full-stack systems
• Create solutions that help meet regulatory needs for the company
• Stay current on technology trends, experiment with and learn new technologies
• Participate in internal and external technology communities
• Mentor members of the engineering community
• Code or evaluate code as needed
• Collaborate with digital product managers
• Deliver robust cloud-based solutions that create powerful experiences for millions of Americans
• Use modern programming languages, databases, container orchestration, and AWS tools and services

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems
• Create solutions that meet regulatory needs for Capital One
• Stay current with technology trends, experiment with and learn new technologies, and participate in internal and external technology communities
• Mentor members of the engineering community
• Collaborate with digital product managers to deliver robust cloud-based solutions
• Use Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, open-source RDBMS and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership across multiple teams and shape system architecture and long-term technology direction
• Design and implement large-scale, distributed, or cloud-native systems with high reliability and performance requirements
• Partner with architects and product leaders to define platform roadmaps and shared-services strategy

• Design and build the agentic orchestration layer enabling AI agents to be composed, sequenced, and operated as a unified associate experience
• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems
• Create solutions that meet regulatory needs
• Collaborate with digital product managers to deliver robust cloud-based solutions for millions of Americans
• Provide technical leadership and direction across Agile teams, setting standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify improvement opportunities, implement targeted refactoring, reduce technical debt, and enhance system performance
• Influence long-term technology strategy through evaluation of emerging tools and practices
• Mentor members of the engineering community and participate in internal and external technology communities

Full-stack Engineer 4, Agentic Orchestration

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems
• Create solutions that meet Capital One’s regulatory needs
• Stay current with technology trends, experiment with and learn new technologies, and participate in internal and external technology communities
• Mentor members of the engineering community
• Collaborate with digital product managers to deliver robust cloud-based solutions
• Use Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, open-source relational and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership and direction across Agile teams
• Set standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify improvement opportunities, implement targeted refactoring, reduce technical debt, and improve system performance
• Influence long-term technology strategy through evaluation of emerging tools and practices in a “you build it, you own it” environment

• Design, build, and/or deliver ML models and components solving real-world business problems
• Collaborate with Product and Data Science teams
• Inform ML infrastructure decisions based on modeling techniques, data, feature selection, training, tuning, dimensionality, bias/variance, and validation
• Write and test application code
• Develop and validate ML models
• Automate tests and deployment
• Collaborate on a cross-functional Agile team to create and enhance big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines feeding ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring
• Ensure code is well-managed, models are risk-governed, and ML follows Responsible and Explainable AI best practices
• Use programming languages such as Python, Scala, or Java

Machine Learning Engineer, Senior

Security Engineer

• Leverage LLMs and machine learning to automate detection logic, summarize attack chains, reduce false positives, and accelerate detection development
• Lead design, development, and maintenance of detection rules using Detection-as-Code methodologies, GenAI-assisted workflows, and CI/CD pipelines
• Design and build behavioral detections identifying adversary patterns, TTPs, and anomalous endpoint activity
• Use user and entity behavior signals, process telemetry, and correlation logic to distinguish malicious from benign activity at scale
• Use the MITRE ATT&CK framework to visualize, prioritize, and close endpoint coverage gaps
• Drive detection architecture decisions balancing fidelity, volume, and operational risk
• Conduct hypothesis-driven threat research across enterprise endpoint environments using Red Team methodologies and adversary TTPs
• Translate attacker techniques into high-fidelity detections and proactively identify coverage gaps
• Own end-to-end detection coverage for the Endpoint threat surface, from telemetry onboarding through alert deployment, tuning, and continuous coverage analysis
• Partner with business leaders, CSOC, Cyber Threat Intelligence, and Cyber Threat Hunt
• Ensure documentation meets fintech compliance and audit standards
• Mentor engineers on security concepts, AI-driven workflows, and detection engineering best practices

Detection Engineer Manager, Cyber Security

Manager

• Lead and develop a team of 4–6 Unit Managers who drive call center associate teams
• Lead performance for a specific business element, including budget management, business goals, performance management, staffing plan development, and long-term business goals/vision
• Drive individual, team, and department efficiency and productivity through metric management
• Ensure compliance with third-party management requirements for the repossession agent vendor network
• Develop leadership team members and associates and uphold performance management standards
• Motivate associates and support their career aspirations
• Establish and execute repeatable, efficient team processes
• Maintain team and individual morale through change and development
• Develop and implement process improvements
• Execute quality monitoring requirements supporting customer satisfaction goals
• Work Monday–Friday, 8:00am–5:00pm CT

Senior Dealer Funding Unit Manager

Data Engineer

• Collaborate across Agile teams to design, develop, test, implement, and support technical solutions
• Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Use Python and Spark, open-source relational and NoSQL databases, Databricks, and Snowflake
• Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data-community members
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions
• Independently design, build, and deliver cloud data solutions and applications
• Architect and enforce data engineering design patterns for code quality, maintainability, and reusability
• Communicate technical concepts and data outcomes to internal and external stakeholders
• Design and build scalable, resilient, and operationally efficient data pipelines and platforms
• Implement data security standards including encryption and fine-grained access control, ensuring privacy-regulation compliance

General Counsel

• Provide strategic legal advice on corporate governance matters to Capital One’s Board, Board Committees, senior management, and internal clients
• Monitor governance issues, trends, and topics
• Draft Board and Committee materials on governance-related matters
• Manage director onboarding, orientation, and ongoing education programs
• Provide logistical and legal support for the Board, including agenda setting, meeting execution, minutes, resolutions, scripts, and other documents
• Manage the annual stockholder meeting and prepare related materials
• Administer corporate governance guidelines and other corporate policies
• Lead ad hoc projects with multiple stakeholders
• Manage and coordinate outside counsel when necessary
• Serve as a trusted legal advisor to the Board, its Committees, and senior management

Senior Manager, Assistant General Counsel – Governance & Securities

• Lead a portfolio of diverse technology projects and direct a team of developers experienced in distributed microservices and full-stack systems
• Drive end-to-end design and implementation of large-scale, cloud-native systems with high reliability, performance, and data-design requirements
• Partner with architects and product leaders on system architecture, platform roadmaps, and shared-services strategies
• Direct the design, development, testing, and implementation of intelligent solutions using AI technologies, LLMs, and cloud infrastructure
• Partner with digital product managers to build cloud-based solutions supporting hyper-personalized user experiences
• Use Java, JavaScript, TypeScript, Python, Go, Scala, Node.js, open-source RDBMS, NoSQL databases, Docker, Kubernetes, and AWS ecosystems
• Mentor engineers, conduct code reviews, participate in technology communities, and champion modern engineering practices

Staff Machine Learning Engineer

Senior Manager, Tech Risk & Analysis

Senior Staff Machine Learning Engineer

Director of Participant Enablement

Full-stack Engineer 4 – Enterprise Platform, Marketing Technology

Full-stack Engineer

Full-stack Engineer

Full-stack Engineer 4, Agentic Orchestration

Full-stack Engineer

Machine Learning Engineer, Senior

Detection Engineer Manager, Cyber Security

Senior Dealer Funding Unit Manager

Data Engineer

Senior Manager, Assistant General Counsel – Governance & Securities

Full-stack Engineer 5 – Java, Spring, Kafka, CI/CD, AI tools, Glue, RDS, DynamoDB