Top Machine Learning Jobs in San Francisco Bay Area, CA

Design, build, and deploy machine learning solutions. Collaborate with teams to transform research into practical applications using large datasets.

The Applied ML Engineer will design and scale ML systems, manage production infrastructure, and build tools for data retrieval and analysis in robotics.

As a Machine Learning Engineer I, you will develop and deploy machine learning systems for core relevance signals, collaborating with engineers and product teams.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

The Senior Machine Learning Engineer will build and enhance models and systems for classifying and enriching Internet data, collaborating with various teams to improve data quality and insights.

The Applied AI/ML Engineer will design, implement, and scale models for urban simulations, collaborating with teams to ensure alignment with customer needs and product requirements.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Lead the development and deployment of ML models to optimize pricing and enhance customer experiences. Drive AI strategies, conduct research, and collaborate across teams.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

The Applied Machine Learning Scientist will develop insitro's ChemML platform and integrate AI for drug discovery, collaborating cross-functionally.

The Principal ML/AI Engineer will shape the AI vision, prototype AI systems, and architect an AI-ready technical stack while mentoring teams and collaborating with executives.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The Machine Learning Engineer will develop, optimize, and integrate ML models and systems focusing on KYC/KYB processes, while ensuring compliance and performance optimization in a dynamic environment.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

The role involves developing and deploying ML solutions, focusing on LLMs and deep learning, while ensuring alignment with business objectives and tech best practices.

Design, deploy, and scale ML systems for production at Foxglove, focusing on data infrastructure for robotics, optimizing inference, and building evaluation workflows.

As a Machine Learning Research Engineer, you will research and train models, build agents using proprietary algorithms, and apply techniques to real enterprise datasets.

As a Senior Machine Learning Engineer at Axon, you'll develop AI solutions for public safety, collaborating on training and deploying machine learning models, while ensuring ethical AI development.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

The ML Research Engineer will develop training pipelines for atomistic simulation models and collaborate with researchers to optimize training workflows.

The Machine Learning Engineer will train, fine-tune, and deploy ML models for parsing unstructured data, and build data pipelines for product integration.