Top Machine Learning Jobs in Washington, DC

The Sr. Director of Digital Optimization will lead strategies for CRO and personalization, driving user engagement and business growth across Risepoint's multi-brand ecosystem. Responsibilities include building scalable testing programs, leveraging analytics for insights, and leading cross-functional collaborations.

The role involves producing insights for AI product management, advising clients on AI strategy, and developing business approaches for AI technologies. The analyst will work closely with executives and product managers, driving AI investments and guiding product lifecycle management.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

The DS&ML Group Product Manager oversees Data Science and Machine Learning capabilities, defining strategic vision, managing product portfolios, and ensuring delivery aligned with business needs. Responsibilities include developing roadmaps, executing models, scaling functionalities, and mentoring a team.

Lead AI transformation initiatives in procurement, creating impactful research, developing strategies, and advising clients on AI integration and analytics for business outcomes.

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.

The role involves producing research, leading AI transformation in procurement, engaging clients with actionable insights, and mentoring a team of analysts.

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

The Digital Inside Sales Specialist will identify and close digital transformation opportunities in AI, ML, and automation, focusing on B2B sales within targeted accounts while collaborating with internal teams for technical consultation.

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 role involves leading Gartner's AI technology research, advising clients on AI applications, managing generative AI solutions, and providing actionable insights on AI trends and best practices.

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.