Waymo
Direct Greenhouse career site

Staff Machine Learning Engineer, Driver Refinement & Validation

Location
Mountain View, CA
Listed
Today

You will

  • Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo's business
  • Fine-tune, adapt, and benchmark state-of-the-art generative models to improve autonomous vehicle perception, motion prediction, and trajectory planning
  • Write high-quality, scalable, and thoroughly tested code to bring cutting-edge ML into production
  • Partner with world-class engineers and product managers to deliver safe and smooth autonomous vehicle behaviors

You have

  • MS in Computer Science, Machine Learning, Robotics, or related technical field, or equivalent practical experience
  • 8+ years of industry experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments
  • Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities
  • Expertise with modern deep learning frameworks, such as JAX or PyTorch

We prefer

  • Experience in deep learning, reinforcement learning, and ML systems
  • Domain expertise in solving prediction, behaviors, motion planning, or related robotics problems
  • ML post-training experience
  • Prior industry experience (e.g. internships) in applied ML or software development
  • Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP)

Pay and benefits

The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company's generous benefits programs, subject to eligibility requirements.

Hourly PhD Pay $251,000 - $310,000 USD

About Waymo

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.

Driver Refinement and Validation's (DRV) mission is to build upon the high-quality ML Driver developed by Driver Intelligence, refining its performance to improve autonomous driving in specific, complex real-world contexts and problem areas (e.g., Ride-Hailing contexts). It aims to ensure that the Waymo Driver always computes safe, compliant, comfortable, and useful plans.

As an Engineer in DRV, you will bridge the gap between cutting-edge machine learning and real-world vehicle performance, engineering the validation and onboard systems that ensure the autonomous vehicle reliably executes intelligent and predictable maneuvers.

Read the original posting

From Waymo's careers page, first listed on Rolev.ai on November 12, 2026. Rolev.ai is not the employer.

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Common questions

Where is the Staff Machine Learning Engineer, Driver Refinement & Validation job at Waymo located?

This Staff Machine Learning Engineer, Driver Refinement & Validation position at Waymo is located in Mountain View, CA. Always check Waymo's application page for specific state eligibility or relocation policies.

How do I apply for the Staff Machine Learning Engineer, Driver Refinement & Validation position at Waymo?

This listing links directly to Waymo's Greenhouse application page. You can apply directly on Waymo's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.