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

Design and implement ML algorithms for bidding and ranking systems in ads. Own complete ML systems from conceptualization to production. Collaborate with teams to integrate models and enhance advertising value using AI.

Lead and grow the Machine Learning Engineering team, set technical direction, define team roadmap, and collaborate across product and engineering teams.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

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

Develop and maintain a full-stack platform for computational chemists, focusing on drug discovery through machine learning and data infrastructure. Collaborate with interdisciplinary teams to enhance software tools for visualizing molecules and managing workflows.

Lead roadmap and product strategy for vehicle autonomy. Define autonomy behavior, UX, data and ML lifecycle, benchmarks, and deliver cross-functional capabilities from data collection through deployment and monitoring.

Design and build the data and analytics layer: schemas, pipelines, APIs, dashboards, forecasting and ML models. Deliver usage-based metering, ensure data correctness and observability, and ship customer-facing analytics while raising engineering standards.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Principal Machine Learning Engineer will design and scale ML systems for personalization and search, mentor engineers, and lead major ML initiatives at Fetch.

The Senior AI ML Engineer will design and implement AI/ML systems for healthcare, manage projects from ideation to release, and mentor engineers. Responsibilities include delivering quality code, driving architectural decisions, and collaborating with cross-functional teams.

Develop and implement advanced reinforcement learning methods and distributed systems for AI agents. Collaborate with customers to understand needs and create tailored solutions.

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

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Develop machine learning models for search ranking and personalization at Faire, leveraging data to help local retailers thrive.

Own the full ML lifecycle for ads bidding stack, developing models for auction optimization and collaborating with a team to enhance platform effectiveness.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

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

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

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

Lead design, development, and deployment of end-to-end recommendation systems. Build, tune, and evaluate scalable recommendation algorithms, integrate ML into products, lead projects, mentor teams, and communicate solutions to clients and stakeholders while driving innovation in replenishment and supply chain analytics.

Lead architecture and development of a SaaS platform for data center energy procurement. Build forecasting, contracting, and monitoring modules; implement AI tools on AWS (Bedrock, SageMaker); hire and mentor engineers; translate business logic into scalable systems; deliver demos to investors and customers.

The role involves leading a team of Forward-Deployed Machine Learning Engineers to deliver AI solutions, manage project execution, and enhance operational excellence.