Top Remote Machine Learning Jobs in San Francisco Bay Area, CA

Research Engineer will conduct Machine Learning research to enhance localization and global entertainment, focusing on ASR, Speaker Diarization, and Audio Understanding.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

The Senior Manager, Machine Learning will lead a team of ML engineers and scientists to develop and implement machine learning systems, ensuring they meet product needs and are scalable.

Lead and build a Machine Learning team, driving strategy and execution across product areas like Document Generation and Voice Agents while collaborating with Product and Engineering.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

As a Machine Learning Engineer, you'll evaluate neural network quality, coordinate with researchers, manage experiments, and report results to streamline AI software development.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

Design and deploy machine learning models to combat financial crimes while collaborating with stakeholders and maintaining compliance with regulations.

As a Senior Machine Learning Engineer, you will design and enhance the AI evaluation platform, focusing on data pipelines and model benchmarking systems, collaborating closely with team members.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The Staff Machine Learning Engineer will architect and implement advanced ML solutions, lead ML applications in Messaging and Notification, and mentor engineers within Airbnb's AI innovations.

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

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

The engineer will train, evaluate, and deploy ML models for understanding driving environments, focusing on motion prediction and planning for autonomous vehicles.

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

Responsible for training and deploying ML models for scene understanding, behavior prediction, and planning in autonomous vehicles. Collaborate on designing and analyzing experiments, maintaining evaluation code, and improving model performance.

As a Principal Engineer on the Behaviors team, you will guide the technology direction, lead complex initiatives, and mentor engineers to enhance autonomous vehicle capabilities through ML solutions.

Develop and implement large-scale machine learning models to enhance user ad predictions and better understand user interests through data mining and collaboration with product teams.