Waymo

Builds self-driving AI and runs a robotaxi service

Senior Technical Program Manager - Simulation

Program ManagementConfirmed live in the last 24 hours

Full-time

About the Job

Requirements

A bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
At least 3 years of experience as a Technical Program Manager in a software engineering or large-scale infrastructure environment.
At least 2 years of experience managing technical projects involving machine learning infrastructure, model training and evaluation loops, or machine learning data pipelines.
A proven track record of owning and driving complex technical programs end-to-end, managing timelines, risks, and dependencies across multiple stakeholders.
Strong technical judgment and the ability to engage in design discussions with engineering leads and analyze technical trade-offs.
The ability to convey complex technical concepts to research and infrastructure teams.

Responsibilities

Own and drive the execution of large, cross-functional programs within the Simulation and ML Evaluation domain, translating technical roadmaps into structured project plans.
Drive programs integrating simulation into the machine learning development loop and establish a reliable path for model training, offline evaluation, and validation.
Identify, track, and mitigate technical dependencies, risks, and blockers across onboard software and offboard infrastructure teams.
Contribute technical judgment to tool and platform design discussions, evaluate architectural trade-offs, and ensure deliverable quality.
Coordinate releases, manage tool deployment, and oversee triage workflows for simulation platforms to support reliability and usability for developer teams.
Identify systemic bottlenecks in the offline evaluation loop and implement process or tooling improvements to scale simulation capabilities and efficiency.

Desired Qualifications

Experience with machine learning frameworks such as JAX or PyTorch and cloud-based machine learning training and evaluation platforms.
Familiarity with advanced simulation technologies, including machine-learning-based scene generation such as NeRF, Gaussian Splatting, or Diffusion, and reactive agent modeling.
Familiarity with autonomous system simulation, log playback infrastructure, or closed-loop model validation strategies.
Experience with large-scale dataset management, data validation frameworks, or unified data solutions.
Experience building or managing developer tools or platforms that simplify complex developer workflows.
Prior experience in the autonomous vehicle industry or robotics, including understanding onboard and offboard dependencies.
A master's degree in a technical field, ideally related to AI or machine learning.

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.

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

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range

$196,000—$242,000 USD

Salary Range 196000 - 242000 USD

About the Company

Waymo

Builds self-driving AI and runs a robotaxi service

Waymo builds self-driving technology and uses it to run a ride-hailing service in which passengers summon electric cars with no one behind the wheel. In 2020, it became the first company to open fully driverless rides to the public, starting in metro Phoenix. Its system, the Waymo Driver, pairs cameras, radar and laser sensors called lidar with onboard computers whose AI predicts what nearby people and vehicles will do and drives the car. Riders pay per trip through the Waymo app, or through Uber in some cities, while Waymo and fleet partners keep the cars charged and maintained. Waymo began as a Google project in 2009 and became a separate Alphabet company in 2016; it is based in Mountain View, California.

Company size: 1,001-5,000
Company stage: Debt Financing
Total funding: $32.1B
Headquarters: Mountain View, CA
Founded: 2009

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