Top Machine Learning Jobs in Hampton, VA

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Lead development and evaluation of AI products for medical professionals using large-scale datasets. Create product and client-facing analytics, influence data team strategy, and collaborate with product managers, analysts, and engineers to execute data projects from ingestion through analysis to recommendations.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Administer and secure DCIM database systems (Nlyte Neo), collect/ingest and clean data center equipment/cabling data, build scripts, complex views, reports and Power BI dashboards to visualize power/space/cooling/cabinet utilization, tune performance, document designs and processes, assist software releases, design cloud data solutions, and support enterprise data center portfolio management for mission-critical operations.

The Senior Product Manager will lead the integration of machine learning into search relevance, defining product vision and collaborating with teams to enhance ecommerce search functionality.

As a Sr Director Analyst, you will create actionable research in analytics and AI, advise clients, and lead a team in impactful research. Responsibilities include engaging clients, presenting insights, and mentoring team members in analytics & AI best practices.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

Lead the Data Sources product roadmap for document parsing, fraud detection, and bank aggregation. Drive metrics (parse accuracy, fraud catch rate, connection success, SLAs), write specs, engage clients, mentor PMs/engineers, and represent the platform externally. Prioritize document types, extraction models, reliability, and scalability to improve conversion, client satisfaction, and operational efficiency across mortgage, tenant screening, and government use cases.

Lead product strategy and roadmap for two flagship B2B SaaS solutions in Food Equipment Services. Drive discovery, prioritize AI-driven quoting and design features, partner with engineering and GTM teams, define success metrics, and oversee delivery, adoption, and continuous improvement.

The Senior Credit Risk Manager will oversee credit analysis, experimentation design, performance monitoring, and strategic decision support in the U.S. loans business.

Serve as the primary technical resource for channel partners to enable partner sales through training, demos, PoV engagements, joint account strategy, and creation of repeatable technical assets and reference architectures. Influence product roadmap via partner feedback and represent 7AI at events to scale partner-led pipeline and long-term customer success.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Serve as technical lead in pre-sales for identity verification and fraud prevention. Lead discovery, workshops, POCs, demos, and solution design; advise on risk/compliance; align cross-functionally; influence product; mentor junior consultants and contribute thought leadership.

Lead end-to-end post-sale value stream (implementation through renewal), design the I2R operating model, govern AI/agentic systems, drive retention and time-to-value, partner across Product/Finance/Engineering, apply SAFe and LPM to scale automation and measurable outcomes for adoption, churn reduction, and renewals.

Analyze historical demand, occupancy, transactions and competitor pricing to optimize daily, monthly, and event pricing. Build dashboards, deliver revenue insights to leadership, and collaborate with Operations and Marketing to implement pricing and promotional strategies while maintaining data integrity.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

The Artificial Intelligence Integrator will facilitate AI integration in NATO's military strategy, collaborating with experts, developing AI applications, and enhancing wargaming capabilities.

Lead the Data + ML Platform team to design, build, and operate scalable data and MLOps infrastructure. Drive platform strategy, enable ML experimentation-to-production workflows (model registry, feature stores, drift monitoring, experiment tracking), modernize streaming and batch pipelines, and scale the team while partnering cross-functionally to deliver measurable outcomes.

Lead cross-functional strategic projects, build quantitative models and dashboards to track KPIs, align technical and commercial teams, audit and design scalable operational workflows, and synthesize technical and financial data into leadership-level presentations.

AVIA seeks experts in Digital Health and AI for advisory roles to support healthcare systems' technological transformations as part-time, project-based consultants.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

This role involves designing, deploying, and maintaining machine learning and AI models in production, managing ML pipelines, and ensuring system reliability and performance.

The AI Developer is responsible for designing and deploying AI solutions, including autonomous agents and predictive models, and integrating them into business operations.