Top Machine Learning Engineer Jobs in San Francisco, CA

Design, implement, benchmark, and optimize CUDA-based GPU kernels and custom operators for on-vehicle ML inference. Build profiling/debugging tooling, integrate kernels into the ML runtime, collaborate with cross-functional teams, and deliver production-grade high-performance libraries meeting strict latency, throughput, and reliability targets.

Lead architecture, design, and delivery of scalable LLM-based solutions (RAG, vector DB, agentic workflows, PEFT). Own full SDLC, cloud and Databricks deployments, DevOps automation, prompt/response guardrails, and cross-functional collaboration to ensure performance, security, and reliability.

Technical leader who architects and delivers end-to-end ML and computer vision pipelines to reconstruct and maintain map primitives from multi-modal vehicle sensor data, driving national-scale, production mapping systems and cross-functional integrations.

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.

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.

Design, build, and operate an AI-powered customer engagement platform that personalizes outreach using product telemetry and business data. Create predictive customer scoring models, segment cohorts, integrate CRM/marketing/analytics systems, automate offer triggers, measure program effectiveness, and iterate quickly with Retool and AI tools to drive retention and expansion.

Design, build, and operate an AI-powered customer engagement platform that uses telemetry and business data to personalize outreach, create customer scoring models, segment cohorts, surface offers, integrate CRM/marketing/product analytics, and measure and iterate on program effectiveness.

Design, build, and operate an AI-powered customer engagement platform that uses product telemetry and business data to generate personalized outreach, build and backtest predictive scoring models, identify cohorts and trigger targeted offers, integrate CRM/marketing/product analytics, measure program effectiveness, and iterate quickly using Retool prototypes to drive retention and expansion.

Lead technical direction and architecture for DAP Repository Flows, design autonomous/scheduled agents acting on codebases, improve onboarding experience, partner across teams, mentor engineers, and solve high-scale systems problems to deliver AI-powered automation on repositories.