Top Machine Learning Jobs in Hampton, VA

Performs data science projects involving statistical modeling, machine learning, forecasting, data cleaning, exploratory analysis, and AI-assisted workflows. Builds and maintains models, pipelines, reporting, and analytics-ready datasets using Python, SQL, Snowflake, and dbt. Supports validation, documentation, testing, governance, and stakeholder communication while developing proficiency in modern data science tools and deployment practices.

The Senior Business Development Representative will generate enterprise sales pipeline through account research, lead identification, outbound calls, emails, and social outreach. The role qualifies opportunities, maintains accurate Salesforce records, represents Rasa’s AI platform, collaborates with sales and marketing teams, and works toward exceeding quotas. This fully remote position requires strong communication, organization, customer empathy, autonomy, and comfort working in a fast-paced startup environment.

Own the strategy and roadmap for Constructor’s search quality and Product Discovery Engine. Drive measurable improvements in relevance, conversion, revenue per visit, and GMV across retail verticals. Partner with ML, data science, and engineering teams to productionize state-of-the-art retrieval, ranking, query understanding, personalization, and LLM capabilities. Establish evaluation frameworks, investigate quality issues, align multiple teams, and expand into chapter-wide product leadership.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Owns operations for Optain’s nationwide network of contracted optometrists and ophthalmologists. Responsibilities include creating provider policies and SOPs, running quality and performance programs, modeling capacity, managing recruitment, handling complaints and urgent findings workflows, and preparing governance decisions for the Medical Director. The role partners with Product and Engineering to automate network processes and requires experience in healthcare operations, clinician networks, clinical quality, credentialing, and multistate licensing.

Administer, design, test, secure, patch, and implement Linux-based systems and workstations supporting Air Force Intelligence Operations. Develop Ansible automation, troubleshoot RHEL environments, validate system changes, and contribute to virtualization, cloud, monitoring, and secure-access solutions. The role requires collaboration with customers to translate mission needs into resilient technical capabilities across global, multi-infrastructure systems.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead the technical direction of Quora’s recommendation ecosystem, including feed retrieval, ranking, re-ranking, optimization, data pipelines, feature engineering, model training, and production integration. Drive measurable improvements through experimentation, apply generative AI, mentor engineers, and partner across product, data science, and infrastructure teams.

Leads delivery of large-scale AWS and digital transformation programs, overseeing planning, execution, reporting, risk mitigation, quality, and customer outcomes. Manages multi-functional teams of business analysts and engineers, develops product and service roadmaps, drives continuous improvement, and resolves customer issues. The role also involves people management, recruiting, coaching, business development, stakeholder communication, and aligning program portfolios with organizational strategy.

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.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Serve as the primary business intelligence and analytics partner for Governance, Risk & Assurance and the General Counsel Strategy Office. Analyze complex datasets, build dashboards and data models, support data governance and risk initiatives, identify automation and AI opportunities, and translate technical findings into business recommendations. Collaborate across enterprise functions, provide reporting and technology guidance, evaluate AI solutions, and drive adoption of data-informed practices.

Design, develop, and operate scalable software platforms and automation for Azure network qualification infrastructure. Build tools for device provisioning, configuration, lifecycle management, testing, telemetry, and health validation. Develop AI-powered agents for troubleshooting, root-cause analysis, and engineering productivity. Create reliable distributed systems with observability, diagnostics, automated recovery, and scalability while collaborating across software and network engineering teams.

Develop and implement agentic and generative AI solutions, including LLMs, RAG, AI security, and related platforms. Support research and development, technical proposals, prototyping, and client consulting. Apply data science and engineering best practices, integrate and analyze data, gather requirements, and translate technical concepts for clients and stakeholders.

Leads global Customer Success for enterprise cybersecurity SaaS customers, owning onboarding, adoption, retention, renewals, expansion, advocacy, and customer satisfaction. Develops scalable CS strategies, support processes, KPIs, AI-driven workflows, adoption programs, and executive engagement frameworks. Partners with Sales, Product, Engineering, Finance, and Marketing while managing teams across the US and India. Drives GRR, NRR, product adoption, customer value realization, and referenceability.

Develop marketplace intelligence, forecasting, ranking, recommendation, personalization, and experimentation models for Airbnb’s search and marketplace products. Partner with product and engineering teams to launch AI-driven improvements, build scalable modeling pipelines, evaluate product changes, and guide technical direction. The role requires causal inference, machine learning, strong SQL and Python or R skills, cross-functional communication, and autonomous leadership of data science roadmaps.

Develop machine learning and statistical models to identify, measure, and manage credit and fraud risk. Partner with stakeholders to translate requirements into scalable solutions, analyze large application and transaction datasets, deploy end-to-end models, and improve risk decision-making. The role requires advanced Python or R and SQL skills, expertise in fraud and underwriting models, model deployment, statistical methods, and mentoring junior data scientists.

Leads marketing and sales analytics strategy, architecture, and measurement. Builds data models, pipelines, machine learning datasets, attribution and incrementality models, and revenue-performance analyses. Advises leaders on investments, tools, account prioritization, and funnel economics. Establishes data, metric, testing, and privacy standards; partners with Marketing, Sales, Finance, Revenue Operations, Data Engineering, and IT; plans roadmaps; presents recommendations to executives; and mentors analysts and engineers.

Own product outcomes for an AI-native cloud infrastructure platform. Conduct customer discovery, frame problems, prioritize opportunities, prototype solutions, analyze product and business data, and collaborate with Design, Engineering, Sales, Customer Success, and Marketing. The role requires enterprise B2B product judgment, technical fluency across cloud infrastructure and FinOps, strong commercial awareness, AI-assisted workflows, outcome measurement, and end-to-end ownership from strategy through iteration.

Build and deploy production machine learning systems for personalized recommendations, fraud detection, risk scoring, ranking, classification, and anomaly detection. Own the full ML lifecycle, including mathematical formulation, feature engineering, training, evaluation, A/B testing, deployment, monitoring, and reliability. Develop low-latency real-time inference services using large-scale donor and transaction data, collaborate with Platform and DevOps teams, and mentor engineers on ML best practices and scientific rigor.

Lead engineering for Fetch’s audience products, building scalable lifecycle services, predictive and lookalike model workflows, identity matching, partner and DSP activation, monitoring, governance, and access controls. Set technical direction, make architectural decisions, guide engineers, and partner with Data Science, Product, and Data Platform to move audience models from prototypes into reliable production systems.

Supports the design, validation, and operationalization of predictive, machine learning, and AI models. Analyzes structured and unstructured data, develops algorithms, validates outcomes, creates visualizations, and communicates findings to stakeholders. Collaborates cross-functionally to integrate solutions and prepares model pipelines for business use. The role also involves statistical analysis, NLP, exploratory data analysis, feature engineering, and research into emerging technologies.

Lead discovery and development of intelligent payment products using data science and machine learning. Analyze large-scale transaction data to optimize routing, interchange, acceptance, fraud risk, supplier connectivity, customer acquisition, and payment economics. Build predictive models, recommendations, optimization signals, and decisioning capabilities; validate business value through experimentation; and partner with Product and Engineering to productionize solutions. Provide technical leadership, mentor analysts, and advise senior Payments stakeholders on high-value opportunities.

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.