Senior Machine Learning Engineer, Fleet Monitoring & Response
Waymo
CA$213,000 - CA$263,000 / year
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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.
You will:
- Design, scale, and optimize Waymo's real-time Fleet Monitoring and event response engine to support expansion to global operating locations.
- Develop and deploy spatial-temporal anomaly detection models (e.g., S2-cell statistical regressions) and leverage Multimodal Foundation Models (Gemini/VLMs) to detect, triage, and automatically respond to off-nominal operations.
- Build and standardize the ML infrastructure for fleet monitoring models, including automated training/inference pipelines, low-latency spatial data stores (e.g., in-memory S2 grids), and continuous model drift monitoring.
- Partner with Product Data Scientists to productionize, evaluate, and scale experimental models, translating notebooks and prototype algorithms into production-grade systems.
You have:
- BS degree in Computer Science or equivalent practical experience.
- 6+ years of experience programming in backend coding languages such as Java or C++.
- Experience in building backend platforms supporting multiple product use-cases/services.
- Prior Machine Learning Engineering experience in Python using mature ML frameworks such as TensorFlow, PyTorch or Keras.
We prefer:
- MS in Computer Science, or equivalent practical experience.
- Experience building and deploying ML / Optimization models into production environments.
- Experience developing ML data pipelines and ML workflow automation code on top of a mature ML infra.
- Experience working at another Ride hailing or Marketplace company.
- Coursework background in ML and Optimization.
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.
Benefits
- stock options
- bonus
About this role
Waymo is seeking a Senior Machine Learning Engineer to build and scale the real-time systems that monitor its autonomous fleet and respond to operational anomalies as the company expands globally. The role combines backend infrastructure work with applied ML: you'll design spatial-temporal anomaly detection models, integrate multimodal foundation models for event triage, and construct the data pipelines and low-latency stores that keep these systems running at scale. This is fundamentally about taking experimental ML work from data scientists and turning it into production-grade systems that handle live fleet operations.
The position requires solid backend engineering chops—six or more years with languages like Java or C++—paired with hands-on ML experience in Python using frameworks like TensorFlow or PyTorch. You should have a track record building backend platforms that serve multiple products, and ideally have shipped ML models to production before. Experience in ride-hailing or marketplace companies is valued, as is formal training in ML and optimization.
This is a remote role based in San Francisco, offering a salary range of $213,000 to $263,000 plus eligibility for annual bonuses, equity, and company benefits. It suits engineers who are comfortable straddling the line between infrastructure and machine learning, and who want to work on systems with real operational stakes.
How this employer is doing
solid
- News: Growing or Expanding
- H1B: Active Visa Sponsor
- Expanding
- New Product/Innovation
In the news
Waymo’s Expansion Is Putting Uber and Lyft Drivers on Notice, Autoblog
This role's local market on JobMinglr
Pay for this role
$213,000 to $263,000 per year
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