Role Overview
Waymo is hiring a Technical Lead Manager, Prediction, ML Evaluation. This is a full-time role in Mountain View, CA, USA; San Francisco. Part of Waymo's Data Science hiring, posted 3 weeks ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Salary Context
Salary is not disclosed in this posting. Market median for Mid-level Data Science roles is $126k-$180k (based on 101 comparable listings). Many employers share specifics during the interview process or after an initial screen.
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Job description
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.
The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver’s behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently.
We have an exciting opportunity for a Staff Technical Lead Manager to lead our ML Evaluation team. In this role, you will define the strategic vision for our evaluation platforms, scaling the critical infrastructure and metrics required, and partner closely with the modeling teams to rigorously validate our next-generation deep neural networks and accelerate ML developer velocity across PrePlan.
You will:
- Influence the strategic direction of foundational infrastructure and evaluation platforms to robustly support next-generation ML model evaluation use cases
- Collaborate cross-functionally with ML engineers, data scientists, and infrastructure teams to identify, define, and surface critical signals on model, component, and system-level performance
- Leverage and scale evaluation and infrastructure platforms to significantly enhance the ML developer experience, enabling faster iteration through earlier, more reliable, and trusted model evaluation
- Manage and mentor a focused team of engineers, aligning their career growth and aspirations with critical organizational needs
- Drive best practices and leverage deep technical awareness of the Alphabet ML stack (e.g., TensorFlow, JAX, Flax, Apache Beam) to optimize evaluation workflows
- Stay at the forefront of emerging technologies, industry trends, and research in ML evaluation methodologies and advanced metrics design
You have:
- M.S. in Computer Science, Mathematics, or equivalent industry experience in Robotics or large-scale ML systems with critical evaluation needs
- 5+ years of experience building and maintaining large-scale distributed infrastructure, ML inference systems, or evaluation platforms, including 3+ years of engineering management experience
- Strong coding and testing proficiency, specifically in Python and C++
- Strong foundational knowledge of model evaluation and core data science principles (e.g., confidence intervals, outlier identification, curve fitting, and causality analysis)
- Familiarity with large-scale ML deployment and orchestration tools (e.g., TF Serving, TorchServe, Kubeflow, SageMaker Pipelines, or Vertex AI Pipelines)
- Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow
We prefer:
- Experience developing and maintaining evaluation pipelines for ML models
- Experience deploying and supporting machine learning models for computer vision, natural language processing, robotics/motion planning, or recommendation systems
- Experience supporting a small team of MLEs developing high-capacity, production-grade models and components
- Strong understanding of metrics computation and regression detection at scale
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.
About Waymo
Waymo
waymo.com
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Frequently Asked Questions
How do I apply for the Technical Lead Manager, Prediction, ML Evaluation position at Waymo?
Use the Apply button above to submit your application directly to Waymo. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Technical Lead Manager, Prediction, ML Evaluation position at Waymo located?
This position is based in Mountain View, CA, USA; San Francisco. Waymo has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Technical Lead Manager, Prediction, ML Evaluation at Waymo earn?
Waymo has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Technical Lead Manager, Prediction, ML Evaluation role at Waymo posted?
This role was posted on June 27, 2026 (27 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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