Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
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.
In this hybrid role, you will report to a TPM Director.
You will:
- Strategic Leadership & Vision: Partner with Simulation, ML Research (AI Foundations), Perception, and Planner leadership to define and drive the long term vision and strategy for Waymo's Simulation and ML Evaluation platforms
- 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
- Transformational Program Delivery: Lead complex, cross functional programs to platformatize and scale evaluation infrastructure, incorporating ML based simulation and advanced technologies to accelerate developer velocity
- Resource & Capacity Optimization: Own program resourcing, budget allocation, and capacity planning for the Simulation and Evaluation domain, forecasting future compute/infrastructure needs and optimizing utilization
- Influence & Alignment: Navigate ambiguity and manage critical upstream/downstream dependencies across organizational boundaries, serving as a trusted technical partner to Engineering and Product leadership
- Team Development & People Management: Build, mentor, and lead a high performing team of Technical Program Managers, fostering a culture of technical excellence, accountability, and continuous professional growth
You have:
- 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
- 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
- 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
We prefer:
- 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
- Scale Infrastructure: Experience with cloud based ML platforms, high performance computing (TPUs/GPUs), and large scale data management and validation
- ML Based Simulation: Familiarity with advanced simulation technologies, including ML based scene generation (e.g. NeRF, Gaussian Splatting, Diffusion, etc.) and reactive agent modeling
- 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