Top Machine Learning Jobs in Hampton, VA

Lead machine learning systems for safety and moderation at Reddit, overseeing a team while driving innovation in abuse detection and prevention.

As a Principal Technical Program Manager, you will engage with partners, own the OpenSync roadmap, and manage product activities from definition to release, ensuring alignment with customer needs and market demands.

The role includes developing B2B marketing strategies, collaborating with sales, creating targeted materials, and conducting market research to support growth.

As Government Affairs Manager, you'll drive advocacy strategy, engage with policymakers, and align internal teams on public policy issues affecting identity and technology.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

Seeking a build engineer with strong software engineering skills to manage CI/CD systems and establish best practices for large-scale monorepos for ML applications.

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

Develop and deploy machine learning models for real-time ad systems, optimizing inventory management, targeting, and campaign effectiveness for Netflix's advertising platform.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

The Staff Software Engineer will lead the design and architecture of the AI/ML platform, mentor engineers, and drive technical direction for MLOps infrastructure in healthcare automation.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

As a Principal Machine Learning Engineer, you will lead a team in developing machine learning solutions for ultrasound applications, mentor engineers, and ensure high-quality regulatory-compliant product delivery.

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.

Lead the architecture and development of machine learning systems for personalized care, treatment intelligence, and automation at scale. Collaborate with cross-functional teams and mentor engineers.

Lead a team of ML engineers and software engineers focused on Ads Content Understanding, driving innovation and efficiency in Ads Monetization.

The Principal Product Manager will define and execute strategies for machine learning-driven search suggestions, working cross-functionally to enhance search experiences and align with business objectives.

Develop and deploy machine learning models for fraud detection and prevention, collaborating with teams and ensuring model performance over time.

Lead the design and delivery of ML infrastructure and models, mentor engineers, and drive innovation in AI-powered intelligence at Upwork.

The Senior Machine Learning Engineer will develop full-stack tools, collaborate on research, and build production ML systems, optimizing infrastructure for AI startups.

The Senior Machine Learning Engineer will enhance fraud detection capabilities through ML technologies, improve model performance, and lead high-impact ML projects from experimentation to production.