Machine Learning Engineer Jobs at Waymo with Visa Sponsorship
Waymo hires Machine Learning Engineers to build the perception, prediction, and planning systems behind autonomous vehicles. The company has a consistent track record of sponsoring work visas for this function, supporting candidates through both nonimmigrant and permanent residence pathways.
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Get Access To All JobsLOCATION: 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.
See all 24+ Machine Learning Engineer at Waymo jobs
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Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Waymo Jobs
Align your portfolio to Waymo's technical domains
Waymo's ML roles concentrate on perception, sensor fusion, motion forecasting, and reinforcement learning for autonomous systems. Frame your projects and publications around these areas before applying, since generic ML experience carries less weight than domain-relevant work.
Target roles outside the H-1B cap window strategically
If you missed the H-1B lottery, pursue Waymo openings that open mid-year or late in the fiscal year. A cap-exempt status through a qualifying institution can bridge the gap while you wait for the next registration period.
Use Migrate Mate to surface open ML roles at Waymo
Waymo's sponsored roles move quickly and don't always stay listed long. Search Migrate Mate to filter active Machine Learning Engineer openings at Waymo by visa type so you apply before positions close.
Prepare your specialty occupation evidence before the offer
For H-1B petitions, USCIS scrutinizes whether the role genuinely requires a specific advanced degree. Gather documentation showing your ML role demands graduate-level expertise in computer science, statistics, or a related field, not just a general degree.
Understand the PERM timeline for green card planning
Waymo sponsors EB-2 and EB-3 green cards for ML Engineers, but DOL's PERM labor certification process typically takes 12 to 18 months before the I-140 petition stage. Ask your recruiter when sponsorship typically begins relative to your start date.
Machine Learning Engineer at Waymo jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Waymo JobsFrequently Asked Questions
Does Waymo sponsor H-1B visas for Machine Learning Engineers?
Yes, Waymo sponsors H-1B visas for Machine Learning Engineer roles. The company files petitions through the standard USCIS H-1B cap process each spring, covering initial status and extensions. Candidates already holding H-1B status with another employer can also transfer their petition to Waymo without waiting for the next lottery.
How do I apply for Machine Learning Engineer jobs at Waymo?
Apply directly through Waymo's careers page or find open roles filtered by visa sponsorship on Migrate Mate. Waymo's ML hiring process typically includes a technical screen, coding rounds focused on ML fundamentals and systems design, and a domain-specific round covering robotics, perception, or planning depending on the team. Prepare to discuss prior work on large-scale ML systems in detail.
Which visa types does Waymo commonly use for Machine Learning Engineers?
Waymo sponsors H-1B, H-1B1, and E-3 visas for nonimmigrant work authorization, alongside EB-2 and EB-3 immigrant visa pathways for permanent residence. Australian nationals benefit from the E-3 category, which has no lottery and allows two-year renewable status. Chilean nationals can access the H-1B1, which operates similarly outside the cap system.
What qualifications does Waymo expect for Machine Learning Engineer roles?
Waymo's ML Engineer roles typically require a graduate degree in computer science, robotics, electrical engineering, or a closely related field, along with hands-on experience building and deploying ML models at scale. Familiarity with sensor data processing, neural network architectures for perception tasks, or real-time inference pipelines is commonly expected, particularly for roles tied to Waymo's autonomous driving stack.
How do I think about timing when targeting a sponsored ML role at Waymo?
If you're on OPT, confirm your STEM extension eligibility since it provides up to 24 additional months of work authorization while USCIS processes an H-1B petition. H-1B cap petitions are filed in April for an October 1 start, so offers in the first quarter of the year align best with that cycle. Starting conversations with Waymo recruiters three to four months before your current authorization ends gives both sides enough time to move through the process without gaps.
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