Senior Product Manager, AI Data and Metrics

Waymo’s Product Management Team is a mission-driven team responsible for writing and enacting first-of-their-kind playbooks to bring fully autonomous driving technology to market. Our team develops simple solutions for complex problems by orchestrating cross-functional efforts to safely drive Waymo’s technology and the products it enables forward. We do this by understanding the customer, the business, and the technology. We are humble about the scope of our work, collaborative in our approach to problem-solving, and ambitious about our vision for the future.

This role follows a hybrid work schedule and reports to Rob Speare, Group Product Manager. 

You will:

• Work with a world class team of engineers, data scientists, and machine learning practitioners to shape the platform we use to simulate and evaluate the Waymo Driver
• Understand and champion Eval Developers by deeply embedding with engineers who mine data, build metrics, and validate the Waymo Driver
• Push the boundaries of UX and Generative AI to accelerate Eval development
• Architect Eval DevEx: Forge deep partnerships with Design, Onboard & Systems Engineering to streamline the tools used to mine data and build high-precision metrics

You have:

• Technical Depth: 5+ years of experience in AI-centric products. You are comfortable discussing distributed systems, data infrastructure, and the nuances of training machine learning models
• Product Vision at Scale: A proven track record of decomposing "moonshot" visions into concrete, phased roadmaps
• UX Sensibility: A passion for building simple, elegant interfaces for highly technical users. You understand that developer productivity is a core business metric
• Influential Leadership: Experience managing complex stakeholder environments, from ML researchers to safety boards and executive leadership

We prefer:

• Generative AI & LLM Implementation: Experience building or launching products that leverage Large Foundation Models (e.g., Gemini, GPT-4) or AI agents to automate complex technical workflows
• Platform & Infrastructure Experience: Background in building or managing experimentation platforms, data pipelines, or evaluation frameworks for large-scale production systems (e.g., Search, Ranking, or AV Simulation)
• Quantitative & Analytical Rigor: Ability to partner with Data Scientists to define success metrics for "Evaluating the Evaluator" (e.g., Precision/Recall, Bias/Variance targets for ML metrics)
• Developer-Centric UX: Proven success in UX modernization for highly technical tools, transforming "expert-only" consoles into guided, self-service experiences
• AV or Robotics Domain Knowledge: Familiarity with the unique challenges of autonomous vehicle evaluation, including simulation realism, log-based testing, and safety gating processes