Top Remote Machine Learning Jobs in Richmond, VA

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

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

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

Seeking a Head of Core ML Products to lead the development of AI-driven systems for improved product matching and user experience at Fetch, requiring extensive product management experience.

The role involves designing and scaling ML infrastructure for LLMs, including building training pipelines and deploying models in cloud and on-prem environments. Collaboration with engineers and managing GPU/TPU workloads is key.

The Machine Learning Engineer will build and scale ML models, collaborate with cross-functional teams, and improve real-time recommendations for Stitch Fix's clients.

The Senior ML Engineer will design and deploy large-scale ML systems for personalized recommendations, directly impacting user engagement and revenue. Responsibilities include building models serving 100M+ predictions daily and optimizing data processing pipelines.

The role involves building and optimizing large-scale ML systems for personalized recommendations that drive engagement, retention, and revenue, impacting millions of users daily.

The role involves building and optimizing machine learning systems for ad performance, collaborating with teams to enhance targeting and revenue. Responsibilities include developing algorithms, conducting experiments, and improving infrastructure for scalable ad decisioning.

As a Senior ML Engineer, you will develop and optimize ad algorithms to enhance engagement and revenue, collaborate with teams, and implement scalable ML systems.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

Design and architect AI/ML solutions, build document parsers and classifiers, maintain AI systems, and collaborate with cross-functional teams.

The role involves leading ML/AI solutions, managing technical roadmaps, collaborating with stakeholders, and driving innovation in products and services.

The Applied Scientist will integrate LLMs into production systems, develop NLP and CV models, and lead AI initiatives for wealth.com.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.