Waymo’s Technical Program Managers and Program Managers are accountable for Waymo’s roadmap execution by providing thoughtful cross-functional planning, clarity, and proactive risk management. In the face of complex technical and operational challenges with no established playbooks to follow, we act with thoughtful urgency, driving conversations, discussions, and outcomes. Our team partners closely with every function of Waymo to structure, own and drive work towards real-world deployments of the Waymo Driver across platforms and geographies.

This role follows a hybrid work schedule and reports and you will report to a Director of Technical Program Management.

You will:

• Program Execution: Own and drive the execution of large, cross functional programs within the Simulation and ML Evaluation domain, translating technical roadmaps into structured project plans
• ML Integration: Drive the execution of programs that integrate simulation deeply into the ML development loop, establishing a seamless, reliable path for model training, offline evaluation, and validation
• Dependency & Risk Management: Proactively identify, track, and mitigate technical dependencies, risks, and blockers across onboard software and offboard infrastructure teams
• Technical Judgment: Exercise strong technical judgment to contribute to tool/platform design discussions, evaluate architectural trade offs, and ensure deliverable quality
• Operations & Release Coordination: Coordinate releases, manage tool deployment, and oversee triage workflows for simulation platforms to ensure high reliability and usability for developer teams
• Process Scaling: Identify systemic bottlenecks in the offline evaluation loop and implement process or tooling improvements to scale simulation capabilities and efficiency

You have:

• Education: Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• TPM Experience: 3+ years of experience as a Technical Program Manager in a software engineering or large scale infrastructure environment
• ML Experience: 2+ years of experience managing technical projects involving machine learning infrastructure, model training/evaluation loops, or ML data pipelines
• Program Ownership: Proven track record of owning and driving complex technical programs end-to-end, managing timelines, risks, and dependencies across multiple stakeholders
• Technical Judgment: Strong technical judgment with the ability to engage in design discussions with engineering leads and analyze technical trade offs
• Communication: Excellent communication and interpersonal skills, with the ability to convey complex technical concepts to both research and infrastructure teams

We prefer:

• MLOps & Tooling: Experience with ML frameworks (JAX, PyTorch) and cloud based ML training/evaluation platforms
• ML Based Simulation: Familiarity with advanced simulation technologies, including ML based scene generation (e.g. NeRF, Gaussian Splatting, Diffusion, etc.) and reactive agent modeling
• Simulation: Familiarity with autonomous system simulation, log playback infrastructure, or closed-loop model validation strategies
• Data Management: Experience with large scale dataset management, data validation frameworks, or unified data solutions
• Developer Platforms: Experience building or managing developer tools or platforms that simplify complex developer workflows
• AV Domain Knowledge: Prior experience in the autonomous vehicle industry or robotics, understanding onboard/offboard dependencies
• Advanced Degree: Master's degree in a technical field, ideally related to AI/ML