Top Machine Learning Engineer Jobs in San Francisco, CA

Research, design, develop, and test machine learning and robotic applications for autonomous vehicles. Own the ML lifecycle: data collection, labeling, processing, model design, training, evaluation. Create novel deep learning architectures and use CNNs and Generative AI for perception, kinematics, intent, and trajectory prediction. Integrate multi-sensor data (camera, RADAR, LiDAR, HD maps), optimize models, develop auto-labeling and large-scale data pipelines, and debug fleet perception issues.

Join Notion as a new-grad software engineer focused on AI-powered features. Prototype and ship model-driven product improvements, integrate and productionize models, build monitoring and guardrails, and contribute to evaluation frameworks and experiments to improve model and product quality.

Lead a team of machine learning engineers to develop vertical ads products, enhance ad experiences, mentor staff, and uphold coding standards.

Join the IT AI Automation team to build and harden micro-apps and AI integrations on a governed GCP platform. Contribute to bug fixes, small features, code and design reviews, apply foundational security and software practices, monitor applications, and use AI tools to support development, testing, and documentation while learning from senior engineers.

Lead advanced analytics and ML initiatives for power and renewables products. Align data strategy with product goals, assess business impact, oversee data governance and infrastructure, provide thought leadership, and mentor analytics team while collaborating cross-functionally to deliver measurable customer value.

The role involves architecting LLM systems, developing personalized workflows, fine-tuning models, and collaborating cross-functionally. Requires strong analytical skills and experience in ML/AI systems.