Top Machine Learning Jobs in Washington, DC

The Specialist Solutions Architect will guide customers in architecting ML & AI applications, provide advanced technical support, and collaborate cross-functionally to enhance Databricks' AI offerings.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The Enterprise Account Executive will drive the sales of Sift's fraud solutions to Fortune 1000 companies, engaging with key stakeholders and building custom strategies to address fraud challenges through value-based selling and collaboration.

Lead product strategy for AI-driven security operations, defining the vision and roadmap for agentic workflows, collaborating with teams, and measuring success metrics.

The VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven culture.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead development of end-to-end Machine Learning models for search and recommendation, collaborating with cross-functional teams and leveraging large scale data.

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 Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.

As a Senior Machine Learning Engineer, you will drive AI initiatives, collaborate across teams, and develop scalable ML infrastructure to improve healthcare.

The AI Strategist leads AI initiative ideation and planning, collaborates across departments to define use cases, and ensures alignment with strategic and regulatory goals.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Develop core AI features for an AI-native product, including building LLM features, developing benchmarks, and overseeing the full lifecycle of development.

The Sales Engineer will serve as a technical lead, guiding clients on advanced data integration and analytics solutions in healthcare, impacting revenue and client engagement.

As a Staff Product Manager for Ads Optimization, you will define strategies for campaign performance, collaborate with engineering and data teams, and present insights to leadership, focusing on optimization and automation.

The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.

The Cybersecurity Intern will assist in enhancing security measures, analyzing security data, participating in incident investigations, and supporting vulnerability management while gaining real-world experience in cybersecurity operations.

Seeking a Senior Data Scientist to develop AI/ML models for predictive maintenance and logistics forecasting, ensuring alignment with mission objectives and collaborating within Agile teams.

The Senior ML Engineer will architect ML infrastructure, deploy models, manage data, ensure MLOps practices, and collaborate on data projects with diverse teams.