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

Lead the Performance ML squad, managing and mentoring engineers while driving the development, deployment, and strategy of predictive models for advertising.

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

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

As an Entry-Level Solution Engineer, you will learn to design AI-driven solutions, support implementations, and develop customer engagement skills in a collaborative environment.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

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.

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.

Lead the application of reinforcement learning techniques to enhance models for creative tasks. Require strong programming and machine learning project experience with a focus on user interface.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

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 Machine Learning Engineer, you will develop and deploy adaptive ML systems, collaborate with partners, and lead product strategy.

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

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.

Lead the Applied Machine Learning team at ExtraHop to develop systems for behavioral detection in network security. Manage model design, evaluation, and operationalization while maintaining experimental rigor and collaborating with product teams.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

The role involves designing and deploying strategies for congestion revenue rights, applying quantitative methods, and developing machine learning models.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

The Staff Machine Learning Engineer will architect and optimize data infrastructure for multimodal AI models in oncology, focusing on data management and processing pipelines.