Top Machine Learning Jobs in Washington, DC

The AI Transformation Lead will drive AI delivery capabilities, transforming internal operations and client programs, while embedding AI practices and managing teams to ensure successful implementation and measurable outcomes.

The Head of Fraud will establish risk functions, manage KYC, monitor fraud exposure, optimize transaction models, and collaborate across teams.

The Business Strategy Director will explore new business opportunities, lead transformational projects, and enhance organizational effectiveness while collaborating with senior leadership.

As a Senior Account Executive, you will manage a portfolio of accounts, partner with HR leaders, identify new business, and guide customer satisfaction to enhance account growth. You will develop strategic enterprise-wide strategies and educate customers on TalentNeuron's value proposition.

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

The Sr. FWA Data Analyst analyzes healthcare datasets for fraud detection using SQL, collaborates with product teams, and engages stakeholders, while presenting findings.

The Executive Director of Advanced Analytics & Data Science leads BeOne's strategic vision in data analytics, AI, and machine learning, driving commercial success and innovation while managing a high-performing team and ensuring data-driven decision-making across the organization.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

Design, build, and scale data and ML systems; collaborate cross-functionally; implement data quality and governance frameworks; document data processes.

The Senior Machine Learning Engineer will develop AI products, support feature implementation, and troubleshoot ML services to enhance customer experiences.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.

As a Forward Deployed Engineer, you will develop solutions, embed with customers to identify their real needs, manage deployments, and integrate product improvements.

The Sales Development Representative will identify and research potential clients, execute outbound prospecting strategies, qualify inbound leads, and collaborate with Sales and Marketing teams to enhance lead generation.

Lead and inspire a team of Machine Learning Scientists and Data Scientists at Netflix, focusing on the ads business and media planning. Enhance partnerships, drive success through collaborative projects, and ensure high-quality outputs that align with business goals.

Seeking a leader for the MLIR team at Netflix to drive machine learning innovations, collaborate with various teams, and enhance organizational capabilities.

In this role, you will design and build a platform for large-scale machine learning model training and optimize its operations. You'll create APIs for both ML practitioners and non-experts, focusing on enhancing cost-effectiveness and reliability in machine learning applications.

Research, develop, and productize Multilingual Live Caption and Translation models while collaborating with a cross-functional team to enhance localization.

Lead a data science team to drive consumer acquisition strategies and improve Netflix's signup processes through analytics, experimentation, and machine learning.

Develop and enhance ML infrastructure for LLMs, partnering with multidisciplinary teams to deliver scalable, robust systems impacting user experiences.

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