Machine Learning Engineer Jobs in USA with Visa Sponsorship
Machine learning engineers who build the infrastructure to train, deploy, and monitor ML models at scale are critically needed by US companies operationalizing their data science investments. This role sits at the intersection of software engineering and data science - requiring expertise in feature engineering, model serving, distributed training, and monitoring - which makes it a strong specialty occupation for visa sponsorship. Employers ranging from FAANG to fintech to healthcare AI companies sponsor machine learning engineers because reliable ML infrastructure is what turns experimental models into revenue-generating products. For detailed occupation requirements, see the O*NET profile.
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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 Waymo Mapping team's goal is to build a high resolution map of the world to support safe autonomous driving. We work on creating the map using a combination of automatic and manual techniques and build the infrastructure to store, process, and distribute the map. Our team collaborates with several other Waymo teams that consume map data.
ROLE AND RESPONSIBILITIES
In this role, you will:
- Design, train, and deploy machine learning models to automate the creation of Waymo's HD maps, unlocking scale for the Waymo Driver.
- Apply and advance state-of-the-art ML techniques, including Vision-Language Models (VLMs) and other Generative AI approaches, to pioneer new solutions in mapping automation.
- Own the complete model development lifecycle, from data mining and processing to model training, evaluation, validation, and productionization.
- Collaborate closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to adapt cutting-edge research into scalable, reliable, and production-grade solutions.
BASIC QUALIFICATIONS
You have:
- 4+ years of hands-on experience in Machine Learning, with a strong focus on computer vision and/or deep learning.
- Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
- Demonstrated experience owning problems end-to-end and working across various parts of the systems stack to deliver results.
- B.S. in Computer Science, a similar technical field, or equivalent practical experience.
PREFERRED QUALIFICATIONS
It's a Bonus if you have:
- M.S. or Ph.D. degree in Computer Science or a related discipline.
- Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
- A track record of publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
- Experience with C++.
- Direct experience with mapping or GIS is a bonus but not required.
COMPENSATION
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.
- Salary Range: $170,000—$216,000 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 Waymo Mapping team's goal is to build a high resolution map of the world to support safe autonomous driving. We work on creating the map using a combination of automatic and manual techniques and build the infrastructure to store, process, and distribute the map. Our team collaborates with several other Waymo teams that consume map data.
ROLE AND RESPONSIBILITIES
In this role, you will:
- Design, train, and deploy machine learning models to automate the creation of Waymo's HD maps, unlocking scale for the Waymo Driver.
- Apply and advance state-of-the-art ML techniques, including Vision-Language Models (VLMs) and other Generative AI approaches, to pioneer new solutions in mapping automation.
- Own the complete model development lifecycle, from data mining and processing to model training, evaluation, validation, and productionization.
- Collaborate closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to adapt cutting-edge research into scalable, reliable, and production-grade solutions.
BASIC QUALIFICATIONS
You have:
- 4+ years of hands-on experience in Machine Learning, with a strong focus on computer vision and/or deep learning.
- Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
- Demonstrated experience owning problems end-to-end and working across various parts of the systems stack to deliver results.
- B.S. in Computer Science, a similar technical field, or equivalent practical experience.
PREFERRED QUALIFICATIONS
It's a Bonus if you have:
- M.S. or Ph.D. degree in Computer Science or a related discipline.
- Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
- A track record of publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
- Experience with C++.
- Direct experience with mapping or GIS is a bonus but not required.
COMPENSATION
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.
- Salary Range: $170,000—$216,000 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 Visa Sponsorship as a Machine Learning Engineer
Emphasize production engineering over research
MLE roles focus on deploying, scaling, and monitoring models in production - not just training them. Highlight experience with model serving frameworks like TensorFlow Serving, TorchServe, or Triton Inference Server to stand out.
Target companies with mature ML infrastructure teams
Google, Meta, Netflix, Uber, and Spotify have dedicated MLE teams that build and maintain production ML systems. These companies sponsor H-1B petitions under SOC 15-1252 and understand the engineering nature of the role.
Leverage your dual skill set in interviews
The MLE role bridges data science and software engineering, and that's your selling point. Strong candidates can discuss both model optimization and system design, which is rare and makes employers more willing to invest in sponsorship.
Build MLOps expertise to increase your value
Feature stores, experiment tracking, model monitoring, and automated retraining pipelines are critical MLE skills. Companies building serious ML products need engineers who can operationalize models, not just build prototypes.
Use STEM OPT to prove production reliability
With a STEM-eligible degree, you get up to 3 years of work authorization through OPT. ML systems require deep institutional knowledge to maintain - use that time to become indispensable to your team's production stack.
File under the right SOC code for engineering
MLE roles typically file under SOC 15-1252 (Software Developers), emphasizing the engineering and systems side of the work. This classification has strong precedent for H-1B approval - ensure your job description reflects the production engineering focus.
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Find Machine Learning Engineer JobsFrequently Asked Questions
What ML infrastructure skills are most valued by employers sponsoring machine learning engineers?
Experience with distributed training frameworks (PyTorch Distributed, DeepSpeed), model serving platforms (TensorFlow Serving, NVIDIA Triton, ONNX Runtime), and feature engineering tools (Feast, Tecton) are the most sought-after skills. Knowledge of GPU cluster management, inference cost optimization, and monitoring for data drift also carries significant weight. These specific technical requirements are exactly what make the visa petition strong, because they show the role requires specialized knowledge beyond general software engineering.
Do machine learning engineers need a PhD, or is a master's degree sufficient for sponsorship?
A master's degree is sufficient for the vast majority of ML engineering roles, and many positions only require a bachelor's in computer science or a related field. A PhD is more commonly expected for research-focused ML positions, not engineering roles focused on production systems. That said, a master's degree qualifies you for the additional 20,000 H-1B cap exemption slots reserved for U.S. advanced degree holders, which improves your lottery odds.
I have a research background but want to move into ML engineering. How does this affect sponsorship?
The transition is common and does not create visa issues. Your research background demonstrates the theoretical knowledge needed to make sound infrastructure decisions, while any production-adjacent work from your research (deploying models, building data pipelines, optimizing training runs) shows practical engineering capability. If you have a PhD, you benefit from the advanced degree H-1B exemption. The combination of theoretical depth from research and hands-on engineering skills can actually strengthen your petition.
How to find Machine Learning Engineer jobs with visa sponsorship?
To find Machine Learning Engineer jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, startups, and research institutions that commonly hire ML engineers on H-1B, O-1, or other work visas. These employers often need specialized AI/ML expertise and are willing to sponsor qualified candidates with relevant experience in data science, neural networks, and algorithm development.
Which companies sponsor machine learning engineers most actively?
Companies operationalizing ML at scale are the most active sponsors. This includes large tech firms (Google, Meta, Amazon, Microsoft), ML-first product companies (Spotify, Netflix, Uber, Stripe), and AI infrastructure startups (Databricks, Anyscale, Weights & Biases). Fintech and healthcare AI companies are also growing sponsors. Look for employers whose products depend on reliable ML systems in production, as they are most motivated to invest in sponsorship for engineers who can bridge the gap between a trained model and a live product.
What prevailing wage levels typically apply to ML engineering roles?
ML engineering salaries typically place candidates at Level 3 or Level 4 of the Department of Labor prevailing wage system, which is favorable for visa petitions. Higher wage levels signal to USCIS that the role is senior and specialized, reducing the risk of a Request for Evidence. If an employer offers a salary at Level 1, that is a red flag for both immigration risk and fair compensation. You can check prevailing wages for your role and location on the DOL's Foreign Labor Certification Data Center.
What is the prevailing wage requirement for sponsored Machine Learning Engineer jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage", the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level. For example, a machine learning engineer in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search Page.
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