Top Machine Learning Jobs in Washington, DC

Lead and deliver complex, cross-team AI product programs, drive agent-first SDLC adoption, ensure integration and operational readiness of AI workflows, define metrics, communicate risks and status, and standardize TPM best practices across Product and Engineering.

Design, develop, and implement secure, scalable cloud systems (Azure/AWS); perform system engineering, risk assessments, and NIST-compliant ATO/ATD processes; manage secure data ingestion and orchestration; integrate AI/ML concepts; secure communications and network infrastructure; present technical findings to senior USG leadership and provide hands-on support.

Lead end-to-end healthcare fraud investigations for Clover's Medicare Advantage business. Own caseloads, gather and analyze claims and medical evidence, coordinate legal support, prepare defensible referral packages, leverage AI and analytics tools, and collaborate cross-functionally to drive recoveries and provider actions.

Lead architecture and implementation of high-performance software to deploy and operate AI/ML models for network threat detection. Build autonomous AI agent workflows, production ML pipelines, and services; drive cross-team engineering standards, mentor engineers, and represent technical direction to leadership.

Develop and maintain scalable, performant web applications and data pipelines. Collaborate with engineering managers, product, and stakeholders using Agile practices. Emphasize observability, testing, CI/CD, security, and incremental releases to deliver robust production systems.

Contribute data science and statistical expertise to design analytical challenges, create high-quality training data, evaluate AI-generated solutions, build evaluation frameworks, and collaborate with researchers to improve LLM quantitative reasoning and model performance.

Design, prototype, and deploy production-ready AI products using ML and generative AI. Lead cross-functional teams, collaborate with stakeholders to solve workflow problems, build scalable prototypes and proofs-of-concept, and apply latest ML/GenAI research techniques.

Own growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. Productize ML capabilities into creator-facing workflows, partner with research and engineering, run experiments and analytics (e.g., Amplitude), conduct customer research, and leverage AI tools to accelerate shipping and internal insight systems.

The role involves developing market intelligence for cyber offerings, supporting technology partnerships, and shaping decision-making materials for senior leadership.

Evaluate and strengthen AI model behavior on cybersecurity topics by writing expert prompts, annotating and grading model responses for accuracy and safety, and applying structured guidelines to classify sensitive content. Work part-time on AI safety tasks with emphasis on secure, responsible handling of dual-use information.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Design, develop, test, and deploy RPA/AI agent solutions (UiPath/Blue Prism) integrated with enterprise systems. Analyze business processes, estimate feasibility, create maintainable automation workflows, document solutions, support UAT/rollout, and troubleshoot production automations. Collaborate with stakeholders, manage integrations (APIs/SQL/WebServices), and ensure quality using unit testing and source control.

The AVP, Digital Portfolio Management oversees P&L for small business products, driving underwriting profitability and digital transformation through analytics, cross-functional collaboration, and strategic initiatives.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Seeking a Senior Full Stack .NET Developer to work on a social good project, with strong skills in C#, AngularJS, design, and UX. Requires 5+ years of experience.

The Data Scientist II will design, build, and deploy machine learning models and data products, translating business problems into data-driven solutions, while collaborating with various stakeholders and ensuring reliable, production-ready outcomes.

The Director of Global Advisory will provide expertise in fraud and financial crime, engage with customers, drive solutions, develop content for thought leadership, and represent BioCatch at events, while collaborating with sales and product teams.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

The AI Solutions Lead will expand Quantiphi's business in key insurance accounts by managing executive relationships, developing account strategies, leading sales initiatives, and ensuring client satisfaction.

Lead the design strategy for client and stylist experiences at Stitch Fix, incorporating AI, managing a design team, and driving product evolution.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Lead a multidisciplinary team to design, deploy, and optimize ML-driven bidding systems and measurement for a nine-figure marketing budget. Drive experimentation, partner strategy, media-mix optimization, and end-to-end measurement while aligning Marketing, Analytics, Engineering, and Product to improve marketing ROI and scale performance.

Lead portfolio-level Data & AI strategy and technical governance for enterprise clients. Advise C-suite, drive architecture and modern data stacks, win high-value engagements, and scale engineering and data science teams.

Join the Offline Infrastructure team to build and maintain large-scale data pipelines, support distributed training (PyTorch, Ray), and improve reproducibility, monitoring, and performance of ML workflows. Collaborate with ML engineers and researchers to evolve the offline ML platform and translate research ideas into production-ready systems.