Top Machine Learning Engineer Jobs in San Francisco, CA

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

Develop and productionize ML models for assessing autonomous vehicle behavior, build ML infrastructure, and collaborate across teams for deployment.

The Machine Learning Engineer role at Patreon involves developing machine learning models, analyzing data, collaborating across teams, and deploying solutions to enhance creator support.

Train personalized ML models, create synthetic data pipelines, evaluate model quality, and develop safeguards for AI privacy and misuse.

As a Senior Applied AI Engineer, you will develop and deploy machine learning models, improve system performance, and drive AI initiatives at Databricks.

In this role, you'll develop machine learning models for logistics optimization, retailer underwriting, and growth strategies, collaborating with a skilled team to enhance the marketplace experience.

Develop mathematical models for discounting systems, collaborate on algorithms, analyze data, and improve rider engagement products while working with cross-functional teams.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Design, train, and evaluate machine learning models for various tasks, optimize pipelines for embedded systems, and collaborate on AI solutions.

The Machine Learning Engineer at Lyft will design, build, and deploy ML models across various domains, collaborating with data scientists and product managers to solve complex business problems at scale.

As a Staff Machine Learning Engineer, you'll lead AI product development, leveraging LLMs and embeddings, collaborating on technical strategy and coding performance enhancements.

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.

Design, build, and ship ML-powered product features (search, personalization, recommendations, computer vision). Improve ML platform, pipelines, deployment, monitoring, and data infrastructure. Collaborate cross-functionally to define metrics, iterate models, and deliver scalable, reliable ML systems.

The role involves building predictive models for blockchain performance and user behavior, implementing solutions, and owning production prediction pipelines.

The VP of Ads Quality Engineering will lead the AI/ML engineering team to improve Pinterest's ads delivery and monetization strategies, collaborating with various departments to develop innovative solutions using machine learning.

Develop and maintain a full-stack platform for computational chemists, focusing on drug discovery through machine learning and data infrastructure. Collaborate with interdisciplinary teams to enhance software tools for visualizing molecules and managing workflows.

The Machine Learning Engineer will propose technical initiatives, lead design discussions, translate challenges into plans, and uphold engineering standards.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Lead development and production deployment of advanced ML and time-series models for water and infrastructure systems, perform research in Physical AI, collaborate cross-functionally, communicate impact to stakeholders, and mentor junior data scientists.