Top Machine Learning Jobs in San Francisco Bay Area, CA

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.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Senior Software Engineer, you'll build AI features focused on LLMs and RAG systems, collaborating across teams to ensure robust performance.

As a Staff Machine Learning Engineer, you will develop models and agents for AI integration into products, focusing on performance monitoring and issue resolution.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

The Machine Learning Researcher will develop AI agents for private equity-backed workflows, focusing on ML cycle efficiency and decision-making.

The ML Engineer will develop and enhance machine learning models for credit decisioning, drive technical innovation, and collaborate across teams to deliver impactful solutions for small businesses.

The Senior Machine Learning Research Engineer will develop and deploy deep learning pipelines, optimize model training, and collaborate with scientists to enhance AI/ML capabilities for cancer detection.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.

We're looking for a Research Engineer to develop ML infrastructure and data systems for medical imaging, focusing on building data pipelines and model deployment.

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 Senior Staff Machine Learning Engineer will architect ML systems for search and recommendations, mentor engineers, and collaborate across teams to enhance content discovery on Patreon.

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

Design, develop, and deploy ML tools and libraries to enhance development and inference for autonomous driving applications, collaborating with cross-functional teams.

As a Machine Learning Engineer, you will build end-to-end ML systems for autonomous underwriting, collaborating with underwriters and engineers to advance ML capability.

As a Machine Learning Engineering Intern at Airbnb, you will drive an AI-focused project, collaborate across teams, and contribute to search relevance and personalization initiatives.

As an AI/ML Engineer, you will design, train, and deploy ML models for flight data analysis, providing actionable performance feedback for pilots.

The role involves developing and optimizing tokenization systems for machine learning, collaborating with research teams, and improving model training efficiency.

As a Machine Learning Engineer, you will apply ML techniques for perception tasks, develop model training methods, and evaluate performance in autonomous driving applications.

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

As a Senior Machine Learning Engineer on the Perception Mapping team, you'll develop ML models for semantic map detection, integrate them into autonomy systems, and lead technical efforts in model validation and best practices.

Responsible for designing and implementing reinforcement learning algorithms, conducting experiments, and optimizing models for robotic applications, collaborating with multiple teams.

Lead the development of machine learning models for lending products, manage a data science team, and ensure compliance with regulations.

The Applied Machine Learning Engineer will build end-to-end ML pipelines, extract insights from data, and optimize systems, primarily using Python and SQL.