Top Machine Learning Jobs in Richmond, VA

The Staff Data Scientist will lead studies using real-world healthcare data to drive drug discovery, collaborating with cross-functional teams and generating patient-centered insights.

The role involves managing relationships with top partners, onboarding them to Runway's platform, analyzing performance, and driving business outcomes through the use of AI technologies.

Lead a team of data scientists to develop and integrate advanced machine learning models for clinical trial execution, improving trial efficiency and patient recruitment.

Manage client relationships for global enterprise clients, providing strategic consulting, performance analysis, and advocating for client needs to drive revenue growth for Pacvue.

As a Product Manager, you will own the product roadmap, ensure project execution, and facilitate collaboration among multi-disciplinary teams to drive innovation in drug discovery.

Develop, optimize, and deploy ML solutions to improve content strategy and performance at Netflix, collaborating with teams across analytics and engineering.

As a Senior Staff Machine Learning Engineer, drive AI safety initiatives, design monitoring systems, and collaborate cross-functionally to ensure robust, safe AI usage in community support products.

As a Staff Machine Learning Engineer, you will design ML systems for location analysis, collaborate with teams to integrate ML into products, and mentor others while ensuring optimal system performance and reliability.

Lead a team of ML engineers to deliver AI/ML solutions on AWS, focusing on practice strategy, operational excellence, and building partnerships.

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

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

Lead the design and execution of ML-based targeting products, improving advertiser outcomes while mentoring junior engineers and collaborating with cross-functional partners.

Lead the design and architecture of GNN and transformer-based multi-entity embedding generation for Reddit's recommendation systems, collaborating across teams and optimizing machine learning pipelines.

Machine Learning Systems Engineers will develop end-to-end 3D machine learning systems, optimize training pipelines, and improve model performance within a collaborative team.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

Drive AI/ML-powered personalized experiences on Pinterest by defining product vision, collaborating across teams, and launching new features to enhance user engagement.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

The Director drives the predictive modeling strategy, mentors others, leads initiatives, and advises on data strategy and innovation in credit risk and collections.

As a Machine Learning Engineer, you will design, develop, and deploy machine learning systems, collaborate on AI features, and ensure reliable production performance.

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Staff ML Ops Engineer builds and maintains infrastructure for ML applications, ensuring they are robust and production-ready, while collaborating with data scientists and ML engineers.

The Staff Software Engineer, AI/ML will design and develop intelligent agents, integrate them with existing systems, optimize performance, and collaborate with product teams, focusing on innovative AI technologies.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

Develop and implement ML algorithms for bioinformatics, debug models, collaborate with teams, and maintain high-quality Python code.