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Machine Learning Engineer, Prediction & Planning

Waymo · Mountain View, CA, USA; San Francisco, CA, USA; New York City, NY, USA · Remote · Active · $175,000–$215,000 / year · Greenhouse

Job facts

FieldValue
CompanyWaymo
TitleMachine Learning Engineer, Prediction & Planning
Normalized title-
Department / teamPlanner (7LU)
LocationMountain View, CA, United States
Work modelRemote / Remote
Employment type-
Salary$175,000–$215,000 / year
Statusactive
ATS providerGreenhouse
Posted / first seen2025-04-28 / 2026-05-29
Changed / last seen2026-06-06 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Waymo.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Mountain View.Open
Department jobsActive postings in Planner (7LU).Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyWaymo
Source44b26b6c-8dfd-437f-a75f-2aba3142363b
ATS providerGreenhouse

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. In this hybrid role, you will report to a manager on our PrePlan team. Team matching happens after you've completed your onsite interviews. You will: Develop the next-generation ML-powered prediction and planning system to enhance the performance and capabilities of the ML driver and support the rapid scaling of Waymo’s business. Frame open-ended, real-world challenges as well-defined ML problems; research, develop, and apply cutting-edge ML techniques, including foundation models and reinforcement learning, for the planning and prediction tasks of autonomous vehicles. Collaborate with world-class researchers, engineers and product owners to create safe, smooth planning behaviors for all road users and to meet product requirements. Develop and evaluate large models, and integrate them into Waymo’s production planning software for real-world applications through close partnership with the Planner and Research teams. You have: BS in Computer Science, ML, Robotics, similar technical field of study 2+ years of experience in Machine Learning modeling and/or Autonomous Vehicles Demonstrated contributions to the ML community through publications, open-source projects, or significant industry impact Hands-on experience with modern deep learning libraries (eg: TensorFlow, JAX, Pytorch) Proficient programming skills (eg: Python, C/C++) Strong analytical and debugging skills We prefer: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field Publications in top-tier conferences such as ICML, NeurIPS, CVPR, ICCV, ECCV, ICLR, IROS, CoRL, ACL, or EMNLP General software engineering experience solving motion planning or related robotics problems Experience applying or evaluating ML-based systems in production environments Experience with performance optimization of deep models, including with respect to specific hardware architectures #LI-Hybrid 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 $175,000 — $215,000 USD

Full job record

Job ID10c3f07e6993ca1e54fa526f8519c8d273ebc075
Org ID3fcf3bd1-54bc-4952-918e-d9d9f3354837
Source ID44b26b6c-8dfd-437f-a75f-2aba3142363b
Board ID44b26b6c-8dfd-437f-a75f-2aba3142363b
Providergreenhouse
Provider Job Key6506689
TitleMachine Learning Engineer, Prediction & Planning
Normalized Title
Statusactive
Activeyes
Location TextMountain View, CA, USA; San Francisco, CA, USA; New York City, NY, USA
DepartmentPlanner (7LU)
Team
Employment Type
Workplace Typeremote
Remote Policyremote
CountryUnited States
RegionCA
CityMountain View
Salary RawSalary Range $175,000 — $215,000 USD
Salary Min175,000
Salary Max215,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://careers.withwaymo.com/jobs?gh_jid=6506689
Apply URLhttps://careers.withwaymo.com/jobs?gh_jid=6506689
First Seen At2026-05-29 22:40:52Z
Last Seen At2026-06-06 20:03:15Z
Last Checked At2026-06-06 20:03:15Z
Last Changed At2026-06-06 07:32:55Z
Inactive At
Source Posted At2025-04-28 22:13:11Z
Source Updated At2026-06-04 18:47:38Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=waymo/date=2026-06-06/2026-06-06T20-03-14-482Z-9ae82cf0fe9f70799413abab7bb6e36d8ef075138c44691cb24f99899f7f0674.json
Event Fields
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Parsed Structured
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Extensions
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Native Structured
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}
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