Machine Learning Jobs at Waymo with Visa Sponsorship
Waymo's Machine Learning teams work on perception, prediction, and planning systems for autonomous vehicles, drawing engineers with deep expertise in neural networks, computer vision, and large-scale ML infrastructure. Waymo has a consistent track record of sponsoring international talent across multiple visa categories for this function.
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LOCATION: MOUNTAIN VIEW, CALIFORNIA, UNITED STATES
JOB TYPE: FULL-TIME
INTRODUCTION
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 Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.
In this hybrid role you will report to a Technical Lead Manager.
Responsibilities
- Create large scale data sets and training recipes, develop methods and recipes for human and machine labeling of data sets
- Develop methods for data mining and recipes for automated data collection/model update flywheels
- Develop methods and recipes for evaluating real-world performance of models, and detecting regressions in model updates
- Understand the data needs of the problem domain team and design scalable infra solutions that support model improvement and product expansion
- Design, build and implement ML data infra and validate the changes to support the continuing scaling of VLM data needs
- Collaborate with ML infrastructure teams and the problem domain team to address issues and bottlenecks and streamline validation
BASIC QUALIFICATIONS
- A degree in Computer Science, Engineering, or a related technical field
- 4+ years of professional experience in the field of software engineering and machine learning
- Proficiency in C++ and Python
- Experience in designing distributed systems processing data at scale, especially ML data infra
- Good foundational understanding of ML principles and SOTA methods
- Passionate about building world-class ML infrastructure
- Strong communication skills
PREFERRED QUALIFICATIONS
- Experience with implementing data compliance & data governance solutions
- Experience with VLM/LLMs
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.
COMPENSATION
- Salary Range: $250,000—$334,530 USD
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.

LOCATION: MOUNTAIN VIEW, CALIFORNIA, UNITED STATES
JOB TYPE: FULL-TIME
INTRODUCTION
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 Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.
In this hybrid role you will report to a Technical Lead Manager.
Responsibilities
- Create large scale data sets and training recipes, develop methods and recipes for human and machine labeling of data sets
- Develop methods for data mining and recipes for automated data collection/model update flywheels
- Develop methods and recipes for evaluating real-world performance of models, and detecting regressions in model updates
- Understand the data needs of the problem domain team and design scalable infra solutions that support model improvement and product expansion
- Design, build and implement ML data infra and validate the changes to support the continuing scaling of VLM data needs
- Collaborate with ML infrastructure teams and the problem domain team to address issues and bottlenecks and streamline validation
BASIC QUALIFICATIONS
- A degree in Computer Science, Engineering, or a related technical field
- 4+ years of professional experience in the field of software engineering and machine learning
- Proficiency in C++ and Python
- Experience in designing distributed systems processing data at scale, especially ML data infra
- Good foundational understanding of ML principles and SOTA methods
- Passionate about building world-class ML infrastructure
- Strong communication skills
PREFERRED QUALIFICATIONS
- Experience with implementing data compliance & data governance solutions
- Experience with VLM/LLMs
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.
COMPENSATION
- Salary Range: $250,000—$334,530 USD
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.
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Get Access To All JobsTips for Finding Machine Learning Jobs at Waymo Jobs
Align your portfolio to autonomous systems problems
Waymo's ML roles center on perception, motion forecasting, and sensor fusion. Publish or present work on lidar point-cloud processing, trajectory prediction, or real-time inference at scale before applying. Generic deep learning projects won't differentiate you here.
Target teams actively recruiting before H-1B registration opens
H-1B registration runs each March for an October start. Waymo needs to select and register you before that window closes. If you receive an offer in January or February, confirm your start date and sponsorship timeline immediately so filing deadlines aren't missed.
Clarify which visa category fits your citizenship
Australian citizens can pursue the E-3 instead of entering the H-1B lottery, which allows year-round filing with no cap. If you hold Australian citizenship, ask the recruiter early whether Waymo will process an E-3 petition rather than waiting for lottery results.
Request USCIS premium processing proactively
Standard H-1B adjudication can stretch several months. Premium processing guarantees a 15 business day decision. For ML roles with competitive offers, ask Waymo's immigration team whether they elect premium processing by default or only on request.
Build a strong research and publication record for EB-2 NIW consideration
Autonomous vehicle ML work often satisfies the national interest waiver standard, which bypasses employer-sponsored PERM. If you have peer-reviewed publications on safety-critical AI systems, discuss the EB-2 NIW pathway with an immigration attorney alongside your employment-based sponsorship.
Find and filter open Waymo ML roles through Migrate Mate
Waymo posts ML roles across seniority levels, and openings fill quickly. Use Migrate Mate to filter verified visa-sponsoring positions at Waymo and set alerts so you apply as soon as a role matching your specialization goes live.
Machine Learning at Waymo jobs are hiring across the US. Find yours.
Find Machine Learning at Waymo JobsFrequently Asked Questions
Does Waymo sponsor H-1B visas for Machine Learnings?
Yes, Waymo sponsors H-1B visas for Machine Learning roles. The company has an established immigration program and works with outside counsel to file petitions for qualifying candidates. If you're subject to the H-1B cap, your offer timeline needs to align with the annual March registration window and an October 1 start date.
How do I apply for Machine Learning jobs at Waymo?
Applications go through Waymo's careers site. Most ML roles require a strong portfolio in perception, prediction, planning, or ML infrastructure. You can also browse and filter open positions that explicitly offer visa sponsorship through Migrate Mate, which surfaces verified sponsoring roles and lets you set alerts when new Waymo ML openings are posted.
Which visa types does Waymo use for Machine Learning roles?
Waymo sponsors H-1B visas for most internationally hired ML engineers. Australian citizens are eligible for the E-3, which has no lottery and can be filed at any time of year. For candidates with strong research backgrounds, employer-sponsored EB-2 or EB-3 Green Card pathways are also available, typically initiated after a period of employment.
What qualifications does Waymo expect for Machine Learning positions?
Most ML roles at Waymo require a bachelor's degree at minimum, though the majority of engineers hold advanced degrees in computer science, electrical engineering, or a related field. Practical experience with large-scale model training, computer vision, or sensor data processing carries significant weight. Research publications or prior work in autonomous systems, robotics, or safety-critical AI are strong differentiators.
How long does the visa sponsorship process take for a Waymo ML offer?
For H-1B, the process runs roughly six to nine months from offer to start date if you're cap-subject, since registration closes in March and employment begins October 1. E-3 petitions for Australian citizens can move faster, often within four to eight weeks of a completed application. USCIS premium processing reduces H-1B adjudication to 15 business days once the petition is filed.
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