Top Senior Machine Learning Jobs in Washington, DC

Lead deep-dive analyses into account takeover and fraud, design and implement real-time defenses, collaborate with product/engineering/data science, run incident response, and deliver actionable insights to protect users while preserving UX and core metrics.

Lead teams in developing computer vision and machine learning solutions for AI dash cameras, focusing on safety insights and risk monitoring. Oversee model lifecycle and collaborate with cross-functional teams for feature deployment at scale.

The Principal Product Manager will lead the Underwriting team to improve credit risk models, manage vendor relationships, and analyze portfolio performance.

The Senior Sales Engineer will drive pre-sales success by combining technical expertise in AI/ML with solution design, customer engagement, and thought leadership, collaborating closely with Sales and Product teams.

The Regional Sales Manager will drive sales of ExtraHop's advanced security platform within the Federal sector, develop government relationships, and exceed revenue targets through strategic account management.

Lead the development of advanced AI models, integrating cutting-edge technologies into healthcare applications while mentoring junior staff and ensuring compliance.

The role involves leading data exploration and analytics projects using statistics and AI methodologies for national security, requiring significant experience in data science and AI.

The Software Engineer will develop AI-powered cybersecurity products, iterating based on feedback, collaborating with research teams, and engaging with customers to inform product development.

As a Senior Data Scientist, you'll analyze data to solve complex problems using machine learning and statistical methods. You'll lead projects, develop algorithms, and work closely with clients to derive insights from data.

As an Analytic Methodologist, you'll lead data exploration and analytics projects for the Department of Defense, applying innovative methodologies and managing complex data analysis.

Lead Unity's Robotics and Industrial strategy, driving product roadmap, cross-functional collaboration, data-driven decisions, and managing partnerships to enhance autonomous system development.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

The Transformation Strategy Lead executes complex workstreams, develops business strategies, manages projects, and creates executive communications, contributing to healthcare transformation initiatives.

As an Enterprise Account Executive at Salesforce, you will drive revenue growth by leveraging AI-driven solutions, understanding client needs, and demonstrating how Agentforce can solve business challenges while fostering client relationships.

The Engagement Manager leads client projects, manages teams, ensures timely delivery, develops client relationships, identifies business opportunities, and provides thought leadership.

The role involves defining AI strategy for the AECO industry, prioritizing AI use cases, and guiding AI initiatives to align with Autodesk's portfolio.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

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

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

The Senior Software Engineer will develop ML training pipelines, maintain cloud systems, and optimize the ML lifecycle for dental products.

Lead the machine learning and personalization efforts at Babylist, managing a team focused on enhancing product recommendations, search, and revenue through ML initiatives.

The Senior ML Ops Engineer will build and maintain infrastructure for AI/ML at scale, manage machine learning models, and support team initiatives while ensuring code quality and engineering standards.

The Engagement Manager manages project execution, collaborates with technical teams on AI solutions, develops client relationships, and coaches consultants.

Research Engineer will develop and optimize machine learning algorithms for defense applications, focusing on edge devices and enhancing autonomy for military systems.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.