Top Machine Learning Engineer Jobs in San Francisco, CA

Work on AI-powered product features using LLMs and embeddings. Prototype, ship, and productionize model integrations, improve model performance/latency/cost, build evaluation frameworks, and contribute to monitoring, reliability, and UX alongside cross-functional teams.

Design, build, and deploy machine learning models for ad targeting, ranking, and bidding optimization. Develop personalization and recommendation systems at scale. Lead incrementality testing, attribution modeling, and experimentation. Optimize models for production latency and scalability, and collaborate with product, engineering, analytics, and business teams to translate objectives into MLOps-ready solutions for Mastercard's AdTech and commerce media products.

Design, train, deploy, and monitor large-scale sequential and deep learning models (including transformers) to personalize growth and marketing experiences using financial and behavioral data. Collaborate with Growth, Product, and Engineering to build scalable ML infrastructure, experimentation frameworks, and production MLOps for real-time and batch systems that improve member engagement.

Lead vision and roadmap for Brain Health & Detection, using AI/ML and telemetry to improve anomaly detection, signal correlation, alert quality, and automation. Partner with engineering and data science to deliver scalable detection models, set success metrics, drive product execution, influence senior stakeholders, and mentor product managers to advance AIOps capabilities.

The Staff Machine Learning Engineer will lead AI product initiatives, optimize ML models for Edge devices, and work with petabyte-scale data, collaborating across teams to enhance customer operations.

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, monitoring, and apply foundational software development and security practices. Gain hands-on experience with Python, SQL, CI/CD, and AI tools while supporting deployments, secrets management, testing, and documentation.

Founding engineer building an AI-native finance automation platform: design LLM-based agents for close, reconciliation, and filings; ensure SOX-compliant, auditable agent workflows; integrate NetSuite/Workday/Anaplan and financial data pipelines; define compliance-grade engineering patterns and partner with FP&A/Treasury to translate spreadsheet workflows into production systems.

As a Staff Machine Learning Engineer, you will explore machine learning techniques, develop scalable systems, mentor junior engineers, and collaborate on strategic projects to enhance AI adoption at Coinbase.

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.

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.