Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Design and maintain KPIs, data infrastructure, and automated reporting to measure operational safety and resilience. Build scalable data models and ETL pipelines, analyze agent response performance, quantify operational capacity, and partner cross-functionally to deliver actionable insights that improve operations and inform AI model training.

Build and maintain data science models and quantitative measurement frameworks to guide infrastructure decisions (chargers, parking, depots). Analyze infra efficiency and identify improvements. Collaborate cross-functionally with Supply Operations, Product, and Engineering to incorporate business context into model-driven decisions supporting expansion to new territories and cities.

Define and own growth metrics (activation, promo redemption, loyalty); build full-funnel performance tracking and paid media tracking infrastructure; provide channel-level reporting to guide marketing and product decisions; ensure data quality and instrumentation; translate business questions into data requirements and perform deep-dive analyses to inform growth strategy.

Lead programmatic media buying and ad ops across DSPs and Google/Apple channels, build in-house programmatic capabilities, deploy AI-driven automation, negotiate PMP/PG deals, and partner with analytics to measure incrementality and feed MMM.

Lead end-to-end ML model development for safety-critical driving behaviors, design experiments, improve data quality, deploy models and metrics fleet-wide, and communicate results across product and engineering teams.

Lead development of data pipelines powering ML for motion planning and decision making. Prototype pipeline and model improvements, fine-tune and evaluate models, deploy and validate models on fleet with monitoring, collaborate with perception/research/simulation teams, and mentor engineers in data-driven reasoning approaches.

The Technical Training Manager will oversee training programs for vendors and partners, ensuring effective delivery and compliance with safety standards, while managing training qualifications and external partnerships.

Lead and grow a Product Data Science team to drive modeling, experiments, and data analysis that improve Waymo Driver performance and operational efficiency. Partner with senior leadership and cross-functional teams to prioritize resources, support geographic expansion, and translate vehicle and operational data into scalable product decisions.

Lead strategy and execution for Waymo's Simulation and ML Evaluation platforms. Integrate simulation into the ML development loop, deliver cross-functional programs to scale evaluation infrastructure, manage resourcing and capacity, align stakeholders, and build and mentor a high-performing TPM team to accelerate model training, evaluation, and validation.

Manage go-to-market plans for product launches, ensuring effective messaging, performance monitoring, and collaboration with cross-functional teams to drive brand growth and user engagement.