Senior Technical Program Manager (Simulation)

Join Waymo, a leader in autonomous driving technology, as a Senior Technical Program Manager (Simulation). In this hybrid role, you will be responsible for driving the execution of large, cross-functional programs within the Simulation and ML Evaluation domain. You will work closely with every function of Waymo to structure, own, and drive work towards real-world deployments of the Waymo Driver across platforms and geographies. You will also proactively identify, track, and mitigate technical dependencies, risks, and blockers, and contribute to tool/platform design discussions.

• 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.
• Program Ownership: Proven track record of owning and driving complex technical programs end-to-end, managing timelines, risks, and dependencies across multiple stakeholders
• TPM Experience: 3+ years of experience as a Technical Program Manager in a software engineering or large scale infrastructure environment
• Education: Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• Communication: Excellent communication and interpersonal skills, with the ability to convey complex technical concepts to both research and infrastructure teams
• Technical Judgment: Strong technical judgment with the ability to engage in design discussions with engineering leads and analyze technical trade offs
• ML Experience: 2+ years of experience managing technical projects involving machine learning infrastructure, model training/evaluation loops, or ML data pipelines
• 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
• AV Domain Knowledge: Prior experience in the autonomous vehicle industry or robotics, understanding onboard/offboard dependencies
• Developer Platforms: Experience building or managing developer tools or platforms that simplify complex developer workflows
• Advanced Degree: Master's degree in a technical field, ideally related to AI/ML