Top Machine Learning Jobs in Richmond, VA

Lead engineering projects and developers building cloud-based, AI-powered risk management solutions. Design and deploy full-stack microservices, APIs, and distributed systems using modern programming languages, databases, AWS services, containers, and messaging technologies. Provide technical leadership across Agile teams, establish engineering standards, mentor engineers, partner with architects and product managers, reduce technical debt, improve system performance, and influence long-term technology strategy.

Lead full-stack engineering projects and developers building cloud-based, AI-powered risk management solutions. Design distributed microservices, APIs, databases, and user-facing systems using modern programming languages and AWS technologies. Provide technical leadership across Agile teams, establish engineering standards, mentor engineers, improve system performance, reduce technical debt, and influence long-term technology strategy while supporting regulatory requirements.

Lead data science for US Card customer management by partnering with data scientists, engineers, product managers, and business teams. Build, validate, and implement machine learning models using large-scale numeric and textual data. Apply statistical modeling, clustering, classification, sentiment analysis, time series, and deep learning to generate customer insights and forecasts. Translate technical findings into business outcomes while contributing to innovation, stakeholder collaboration, and talent development.

Leads engineering projects and developers building cloud-based, AI-powered risk management solutions. Designs distributed microservices and full-stack systems, establishes technical standards, partners with architects and product managers, improves system performance, reduces technical debt, and mentors engineers. The role uses AWS technologies, modern programming languages, databases, APIs, CI/CD, infrastructure as code, automated testing, and observability within Agile teams.

Build AI-driven governance and resilience solutions for enterprise cloud infrastructure. Design intelligent guardrails, distributed systems, microservices, and full-stack platforms using Go, Python, Java, TypeScript, AWS, Docker, and Kubernetes. Lead architectural vision, technical roadmaps, testing, deployment, and optimization while writing code, conducting reviews, mentoring engineers, and collaborating with product, data science, and risk teams.

Develop and deploy machine learning solutions for enterprise risk and anti-money-laundering innovation. Partner with data scientists, engineers, and product managers to build models using structured and textual data, including NLP, graph modeling, deep learning, and Generative AI. Lead projects through design, training, validation, evaluation, and implementation while translating technical findings into business outcomes.

Develop the strategic direction for Capital One’s AI and machine learning platforms. Identify customer and business outcomes, define reusable platform capabilities, build strategy materials, solve cross-functional business problems, and support continuous delivery and improvement of AIML products. The role requires quantitative and qualitative analysis, stakeholder influence, senior leadership communication, people management, and project management.

Build, deploy, scale, and monitor production machine learning models and infrastructure for risk management. Responsibilities include model development, data pipeline construction, cloud and distributed systems operation, Kubernetes-based deployment, CI/CD, model governance, responsible AI, testing, monitoring, and collaboration with product and data science teams.

Develop and implement machine learning models across the full lifecycle, from design and training through validation and deployment. Analyze large numeric and text datasets using Python, cloud computing, and big data technologies. Partner with data scientists, engineers, and product managers to deliver customer-focused products, translate complex analyses into business outcomes, and research emerging methods. Apply statistical modeling, classification, clustering, sentiment analysis, time series, and deep learning techniques.

Lead architecture and technical strategy for a highly resilient enterprise message delivery platform handling billions of monthly messages. Modernize legacy systems, guide build-versus-buy and vendor strategy, establish governance and compliance controls, build workflow automations, and integrate cloud, AdTech, partner messaging, AI, telemetry, and analytics capabilities. Mentor senior engineers, lead architectural reviews, define engineering standards, and drive innovation across message delivery, orchestration, and integration teams.

Build and architect scalable cloud data platforms, pipelines, and applications for Capital One’s Risk Tech organization. Develop distributed data solutions using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Design secure, resilient, and operationally efficient data systems, including streaming and AI-enabled solutions. Collaborate with Agile teams, product managers, engineers, analysts, and data scientists while mentoring peers and communicating technical concepts to stakeholders.

Leads the long-term vision, strategy, architecture, and delivery of Capital One’s automated fraud decisioning platform. Oversees convergence with enterprise decisioning infrastructure, applies LLM and agentic AI capabilities, guides multi-year technical delivery, develops product management talent, manages cross-functional and executive stakeholders, expands platform capabilities across lines of business, and ensures regulatory compliance, risk management, and auditability.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Leads strategy, design, delivery, governance, and adoption of data products for attractions, locations, and non-bookable travel inventory. Defines data entities and relationships to bookable inventory, trips, and customers; integrates third-party data; establishes access patterns and quality standards; and enables machine learning and agentic use cases. Partners cross-functionally to align data products with travel and premium experience initiatives.

Lead strategic product initiatives for Consumer and Developer Experience (CDX), perform consulting-style analysis and analytics, drive AI transformation workstreams, set long-term product vision, develop prototypes with engineering, and build cross-functional stakeholder relationships to align and execute strategic priorities.

Lead product development for a unified enterprise data ecosystem, aligning product, engineering, design, ML, and risk partners. Build data platforms (OneStream, One Lake), improve data trust via automation, scale data products, expand external data use, and deliver real-time intelligent experiences while driving cross-functional alignment and execution.

Develop the strategic direction for Capital One’s AI and machine learning platforms. Identify customer and business outcomes, define reusable capabilities, create strategy materials, align senior leaders and stakeholders, and support implementation and continuous improvement of platform capabilities. The role requires strategic thinking, quantitative analysis, communication, influence, and collaboration across business and AIML teams.

Lead a data science team developing scalable AI and NLP solutions for customer-facing financial applications. Partner with data scientists, engineers, product managers, and designers to build, train, evaluate, fine-tune, and operationalize machine learning and large language models. Drive research into generative AI, training optimization, self-supervised learning, explainability, and RLHF while delivering production systems at scale. Translate technical findings into business outcomes and develop team talent.

Own the vision and roadmap for AI-assisted audit products within the Audit Compass application. Partner with engineering, design, data science, and audit stakeholders to define features, acceptance criteria, user stories, MVPs, and product priorities. Build foundational AI capabilities, understand complex data pipelines, translate business needs into digital products, manage risk, and deliver real-time audit insights in a regulated environment.

Develop and support software, automation tools, dashboards, and alarms for cloud infrastructure, cost attribution, and cloud efficiency. Collaborate with cross-functional teams and senior engineers to design reliable systems, APIs, databases, tests, and AI agents. Contribute to architecture and automation strategies while maintaining strong security, communication, and delivery practices.

Manage a portfolio of advertisers on the Adflow commerce media platform, building relationships, monitoring budgets and campaign performance, presenting business reviews, coordinating onboarding, recommending optimization strategies, and identifying revenue-growth opportunities. The role serves as the primary client contact, collaborates with internal campaign, media operations, creative, and finance teams, and uses performance marketing expertise and analytics to drive advertiser success and long-term partnerships.

Manage a portfolio of advertisers on the Adflow commerce media platform. Responsibilities include client onboarding, campaign coordination, budget and revenue pacing, performance reporting, business reviews, strategic recommendations, optimization feedback, and identifying opportunities to grow advertising spend and channel distribution. The role serves as the primary client contact while collaborating with business development, campaign strategy, creative, media operations, and finance teams.

Lead agile design and development projects for mobile apps and digital products. Coordinate product, design, engineering, marketing, leadership, and client stakeholders; manage project plans, scope, requirements, backlogs, acceptance criteria, deadlines, workflows, and deliverables. Support scoping and client relationship management while ensuring successful end-to-end software launches and alignment with business objectives.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.