Top Machine Learning Jobs in Washington, DC

The Credit Analyst will develop credit risk strategies, manage decision strategies, analyze credit trends, and collaborate with multiple teams to ensure compliance and profitability in credit processes.

Lead the development of machine learning systems for Cedar's Personalization Engine, focusing on ML modeling, MLOps, and team management to drive healthcare solutions.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Product Manager at Vic.ai will lead product strategy and development for AI-driven financial products, collaborating with teams to meet customer needs and improve user experience. Responsibilities include market research, UX championing, and data-driven decision-making.

As a Machine Learning Research Engineer, you'll create critical AI features for the Archie product, collaborating with experts and transitioning AI prototypes into real-world applications. You'll develop AI tools for engineering design and work closely with research scientists.

The Vice President, Employer Business Development & Sales will lead and expand a new business group, focusing on sales and relationships with self-insured employers and brokers, utilizing advanced analytics in healthcare benefits management.

The Senior Machine Learning Engineer will develop, deploy, and optimize machine learning applications, collaborating with cross-functional teams to enhance AI services.

Lead and develop a team in creating AI/ML solutions for transforming communications in real estate. Drive strategy and implementation of new Generative AI solutions.

The Product Manager will shape the outfitting platform, integrate AI capabilities, and define strategies to enhance client personalization and experience.

As a Data Science Intern, you will apply statistical and machine learning techniques to solve problems in the insurance industry, collaborate with experienced data scientists, and present your findings to stakeholders.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

The Machine Learning Engineer will deploy models, improve existing systems, collaborate with teams, and work with large datasets for government clients.

The AIML Director will define the enterprise strategy for AI, Machine Learning, and Generative AI, leading architecture design and delivery of innovative solutions while mentoring a high-performing team.

The Azure AI/ML Engineer will design and implement AI solutions on Azure, focusing on automation, security, and compliance in collaboration with various teams.

As VP of Engineering, you'll lead the application engineering strategy and team, integrating AI capabilities into products while ensuring quality and execution across backend, mobile, and desktop platforms.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Lead Scribd's product strategy for a new Discovery product organization, focusing on search and recommendations through advanced ML systems and user-centered design. Mentor PM teams, oversee the development of AI-driven features, and align product vision with business goals.

Lead the development of agentic AI systems for real estate, focusing on long-horizon, supervised experiences. Architect collaborative systems and define success metrics while mentoring a small team.

Lead the development of intelligent decision engines modeling customer intent in real-time using advanced data science techniques such as causal inference and machine learning. Collaborate with cross-functional teams to optimize systems for search, fulfillment, and customer experience.

As a Machine Learning Engineer, you'll design AI/ML solutions, optimize pipelines, integrate models, and enhance AI capabilities while collaborating with teams.

The Principal Software Engineer will lead multi-year initiatives at SmithRx, focusing on technical strategy, system design, and cross-functional collaboration while mentoring engineers and driving engineering excellence.

Join Clarity AI's Talent Community by submitting an open application for various roles in product, technology, finance, marketing, or operations to drive positive impact.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

Lead product managers overseeing distribution and onboarding experiences, drive product execution, manage a team, and advocate for user needs.