Senior Machine Learning Engineer, Scenes, Traffic Controls
Waymo Open · verified Nov 1, 2026 At a glance
Senior Machine Learning Engineering role at Waymo. Mountain View · $213,000–$263,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Take traffic-control and scene-understanding features from driving data through model development, evaluation and onboard release
- Find rare driving failures in real and simulated data, then create curated training and evaluation sets with suitable labels
- Train and refine multi-task model components, improving their calibration and performance across new regions
- Build evaluation metrics and scenario slices, compare model behavior, and use staged tests to guide launch decisions
- Connect model outputs to the onboard C++ system, investigate driving incidents and coordinate fixes across engineering teams
What you bring
- A CS, electrical engineering, robotics or related degree, or equivalent hands-on experience
- Production ML delivery experience covering model training, offline testing and deployment, with the required experience tied to level
- Strong data pipeline and analytical SQL skills, plus Python, a deep-learning framework and production C++
- Experience owning problems that span data, model development and deployment, with rigorous evaluation and rollout practices
Who this fits
This senior individual-contributor role suits an engineer who can work across data, models and onboard systems. The position is based in Mountain View, California.
From the employer
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
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