Senior Machine Learning Engineer, Scenes, Traffic Controls

RemoteRemoteFull Time$213,000–$263,000 /yrPosted 15 days agoVisa sponsorship available

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Required skills

ML Driver
autonomous driving
ML-powered systems
generative models
Python
C++
JAX
PyTorch
production environments
analytical

Nice to have

deep learning
reinforcement learning
ML systems
applied ML
NeurIPS
ICML

Role summary

Waymo's Driver Refinement and Validation (DRV) team is seeking a Machine Learning Engineer to enhance the autonomous driving ML Driver for complex real-world contexts like ride-hailing. This role involves developing and fine-tuning ML systems, particularly generative models, for perception, prediction, and planning. You will write production-quality code and collaborate with engineers and product managers to ensure safe and smooth autonomous vehicle behaviors. The position requires a Master's degree or equivalent experience in a technical field, proficiency in Python/C++, and experience with deep learning frameworks like JAX or PyTorch in production environments. Preferred qualifications include experience in deep learning, reinforcement learning, ML systems, robotics, and publications in top-tier conferences.

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 a Machine Learning 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.

You will:

Own ML features for Scene Understanding (traffic controls, signs, special regions such as RRX and flood zones, lane states) end to end: data → model → eval → onboard launch

Mine and curate large-scale driving data (real and simulated) to find long-tail failures, build training and eval sets, and design labeling and supervision

Design, train, and iterate on model tasks and heads in large multi-task models. Improve calibration, robustness, and generalization to new geographies

Build rigorous evaluation: PRT metrics, slicing taxonomies, side-by-sides, and staging launches, and turn the results into launch decisions

Integrate models into the onboard stack (C++), combining learned outputs with safe heuristic fallbacks, Mendel-guarded rollouts, and map-contradiction handling

Triage real driving events, find the root cause anywhere in the stack, and propose surgical or systemic fixes. Work closely with Perception, Reasoning, Mapping, and ML Infrastructure teams

You have:

BS/MS/PhD in CS, EE, Robotics, ML, or a related field, or equivalent practical experience.

Hands-on experience shipping ML models to production, including training, offline evaluation, and deployment (L4: 2+ yrs; L5: 4+ yrs, or a PhD plus 2+ yrs)

Strong data mining / data engineering: building large-scale batch pipelines (Beam/Flume/Spark or similar) and analytical SQL to find, slice, and curate data

Proficiency in Python with a modern DL framework (JAX, TensorFlow, or PyTorch) and production C++

Demonstrated cross-stack generalist work: has owned problems that crossed data, model, and systems/serving boundaries

Rigorous evaluation instincts: metric design, error analysis and slicing, and A/B or staged rollout

We prefer:

AV/Robotics experience, especially perception (detection, classification, tracking)

Experience with transformer or temporal models (GRU/RNN), multi-task learning, and model calibration/uncertainty

Labeling-pipeline and supervision design; autolabeling or synthetic data

TPU/accelerator performance work; exporting models for onboard/edge inference

Builds internal tools (visualization, triage, experiment tracking) that accelerate the team

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$213,000—$263,000 USD

Sample Waymo interview questions

1
Design a data ingestion system
system designmedium
2
Design a simulation-based regression detection system for code changes
system designhard
3
Longest Substring with Two Distinct Characters Find the longest substring with at most two distinct characters. Input: s = "ccaabbb" Output: 5 Explanation: The substring "aabbb" contains exactly two distinct characters and has a maximum length of 5.
codingmedium
4
Alien Dictionary Order Derive the alien dictionary order from a sorted list of alien words. Input: words = ["z","x","z"] Output: "" (Empty String) Explanation: The letter 'z' cannot come before 'x' and then suddenly after 'x', creating a cycle and making the dictionary invalid.
codingmedium
5
Palindrome After Deleting One Character Determine if a string can be a palindrome after deleting at most one character. Input: s = "abc" Output: FALSE Explanation: Deleting any single character leaves either "ab", "bc", or "ac", none of which result in a valid palindrome.
codingmedium

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