Top Machine Learning Jobs in Washington, DC

As a Staff Software Engineer, you will lead the development of Cake's AI platform infrastructure, focusing on building, operating, and improving ML systems. The role requires collaboration with customers to address ML challenges and enhance platform capabilities, emphasizing ownership and operational excellence.

The Machine Learning Engineer will design, build, and deploy ML models for data-driven products, collaborating with teams to optimize pipelines and improve performance.

The Sales Account Executive will drive sales for AI software solutions within the Department of War, focusing on military readiness and account strategies.

The Senior Scientist will design small molecules using computational tools, lead projects, manage external teams, and collaborate with machine learning and medicinal chemistry teams.

Lead the Product Safety team in developing safety strategies for autonomous vehicle technology. Oversee safety standards, mentor engineers, and ensure compliance with ISO standards, focusing on safe system development and deployment.

The Director of Product Management will lead a team to manage CAMP's Aircraft Health Management platform, driving product strategy, modernization, and execution with a focus on customer outcomes and market innovation.

The role involves engaging with customers to provide technical guidance, supporting pre-sales activities, developing technical strategies, and managing risks while collaborating with internal teams to align solutions with customer needs.

As an intern, you'll assist in developing edge computing solutions, collaborate with machine learning teams, and improve data processing for satellites.

The AI & Machine Learning Director will lead client engagements, analyze corporate performance, and drive improvements in profitability through machine learning and data analysis, while also managing business development and team collaboration.

The Senior Vice President will lead projects focused on corporate performance, drive revenue growth, and develop business strategies while utilizing data modeling and machine learning techniques for analysis and solutions.

As a Staff Machine Learning Engineer, you'll develop, implement, and optimize ML models to enhance personalized customer experiences, collaborating across teams.

The role involves developing and maintaining machine learning models and infrastructure, defining technical vision, and leading cross-functional initiatives for scalable ML systems.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves designing and maintaining backend systems for ML applications, working closely with cross-functional teams, and optimizing AWS services.

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

Own and execute the billing, financial, and corporate systems product roadmap. Define end-to-end experiences, lead 1-2 scrum teams, prioritize work using qualitative and quantitative data, and collaborate across Finance, Receivables, HR, analytics, UX and commercial teams to deliver automated, data-driven solutions that improve billing and financial functions.

The Machine Learning Engineer will develop and maintain ML deployment pipelines, operationalize AI models, and ensure system reliability and scalability.

The Data Scientist II will design and deploy ML models for autonomous vehicles, enhance data tagging, and improve dataset quality through advanced techniques and frameworks.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.