Top Machine Learning Jobs in Washington, DC

The Staff Product Manager, Conversion ML will shape product strategy for Liftoff's machine learning system, Cortex, develop new ideas, conduct experiments, and adapt roadmap based on data.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead Machine Learning Operations initiatives by developing retail-specific models and a user-friendly Model Workbench for marketers. Ensure product development aligns with customer needs.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

As a Manager in the Finance team, you will support clients in their Finance Transformation using Oracle Cloud ERP and EPM, providing problem-solving, coaching, and analysis to enhance their financial functions with new technologies.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

As a Senior Manager in Cyber Strategy, Risk & Compliance, you will lead teams and projects focused on AI-enabled cybersecurity solutions, providing strategic guidance and managing risks for clients.

As a Senior Manager, you will lead finance transformation efforts, assist with Oracle implementations, manage teams, and ensure client satisfaction.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

Lead the design and implementation of ML training systems, manage a team, promote engineering culture, and drive product development.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and optimize ML models, develop automation playbooks and Falcon API integrations, troubleshoot AI-related issues, support incident response and threat hunting, and deliver customer workshops and collateral. Up to 25% travel.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

Lead Pluralsight's curriculum strategy to identify and shape future skills; translate market and technology trends into a curriculum roadmap; align with product, GTM, and content production; measure portfolio performance with data; lead and develop curriculum directors and managers; define scalable frameworks and represent the company externally.

Lead product vision and roadmap for the Hivemind AI Platform to enable training, evaluation, governance, and safe edge deployment of foundation and domain models. Drive MLOps, data/simulation pipelines, synthetic data generation, model governance, and integration with edge hardware. Partner cross-functionally to productionize research, ensure accreditation and safety, and support continuous learning and sovereign AI factory capabilities for mission-critical autonomy.

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

Lead and grow FAS's AI policy portfolio by setting strategy, managing staff and budgets, overseeing grant-funded projects, building cross-sector partnerships, fundraising, and advising policymakers on AI safety, fairness, responsible adoption, and AI for public missions.

Design, create, and implement AI and ML systems for Defense and Intelligence sectors, ensuring scalability and integration into various environments.

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

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

Design, build, and scale event-driven, distributed backend systems in Python to extract and enrich metadata at massive scale. Lead architecture, mentor engineers, integrate ML/LLM components, optimize performance, and ensure observability and reliability across AWS-based pipelines.