Top Senior Machine Learning Jobs in Washington, DC

As a Staff AI Engineer, you will drive product-centric development of AI technologies, enhance evaluation systems, optimize reasoning strategies, and lead production-grade model tuning while balancing performance and cost.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

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

Lead product managers overseeing distribution and onboarding experiences, drive product execution, manage a team, and advocate for user needs.

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

Lead the design and deployment of AI systems for government applications, focusing on geospatial reasoning and agentic infrastructure. Collaborate with various teams to build reliable machine learning systems.

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

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

As the Data Science Lead for Monetization, you'll shape monetization strategy, lead the data science team, and drive decision-making through measurement and experimentation.

Lead definition and implementation of the companys ML strategy and infrastructure. Build end-to-end production ML systems (data pipelines, training, evaluation, serving), own data strategy and feedback loops, integrate ML with product/backend, write production-quality code, and recruit/mentor the ML team as it scales.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

The Director, Genomics Data will lead genomic data R&D, managing a team to advance data analysis, platform design, and commercialization efforts.

Lead the Opportunity Engine product development, managing cross-functional teams to drive advisor growth and improve client experiences using data and AI.

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.

Develop and optimize machine learning systems for Yahoo News, collaborate with teams to enhance user experience and editorial tools.

Own and close enterprise customer deals, develop expansion opportunities, educate customers on AI architectures, engage with multiple stakeholders, and collaborate with product and engineering teams.

The Senior Principal Product Manager will define the product strategy for ExtraHop's RevealX platform, focusing on enhancing SOC workflows and leading cross-functional execution while mentoring peers and aligning product vision with business goals.

The Senior Product Manager will advance fraud detection capabilities, manage product lifecycles, develop requirements, and collaborate with engineering and data science teams.

The VP of AI will lead the integration of AI into products, drive strategy for AI initiatives, and ensure responsible implementation across the organization.

The role involves managing data to uncover insights, developing predictive models, and bridging clients with data intelligence within the context of evolving market research methodologies.

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