Lead Technical Program Manager (Simulation)

Join Waymo as a Lead Technical Program Manager (Simulation) and play a key role in driving the long-term vision and strategy for Waymo's Simulation and ML Evaluation platforms. You will lead complex, cross-functional programs, optimize resources and capacity, and influence alignment across organizational boundaries. Additionally, you will build, mentor, and lead a high-performing team of Technical Program Managers. This is a hybrid role reporting to a TPM Director.

• Lead the execution of programs that integrate simulation deeply into the machine learning development loop, establishing a seamless, reliable path for model training, offline evaluation, and validation.
• Drive complex, cross-functional programs to platformatize and scale evaluation infrastructure, incorporating machine learning-based simulation and advanced technologies to accelerate developer velocity.
• Own program resourcing, budget allocation, and capacity planning for the Simulation and Evaluation domain, forecasting future compute/infrastructure needs and optimizing utilization.
• Technical Judgment: Strong technical judgment with the ability to contribute to strategic technical direction, analyze architectural trade offs, and balance velocity vs. quality
• TPM Experience: 10+ years of experience as a Technical Program Manager in a software engineering, large scale infrastructure, or ML environment
• ML Domain Expertise: Proven track record of managing complex technical programs involving the Machine Learning platforms (data pipelines, training, evaluation frameworks, or ML infrastructure)
• Program Scale: Experience leading transformational, cross functional programs end-to-end, with a history of managing timelines, risks, and dependencies across senior stakeholders
• Education: Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• Leadership Experience: 3+ years of experience directly managing and developing teams of TPMs or software engineers
• Advanced ML Ops: Experience with large scale model evaluation (e.g. Foundation Models, LLMs, VLMs), closed-loop simulation, and correlating offline metrics with online product performance
• ML Based Simulation: Familiarity with advanced simulation technologies, including ML based scene generation (e.g. NeRF, Gaussian Splatting, Diffusion, etc.) and reactive agent modeling
• Scale Infrastructure: Experience with cloud based ML platforms, high performance computing (TPUs/GPUs), and large scale data management and validation
• Developer Platforms: Experience building or managing ML developer platforms or tooling that simplifies complex engineering stacks
• Organizational Transformation: Demonstrated success in driving organizational change, simplifying interfaces between teams, and improving organizational efficiency
• Advanced Degree: Master's degree or PhD in a technical field, ideally related to AI/ML or Robotics