Machine Learning Engineer Visa Sponsorship Jobs in California
California is the center of machine learning engineering in the United States, with major hiring concentrated in the San Francisco Bay Area, Los Angeles, and San Diego. Companies like Google, Meta, Apple, and a dense ecosystem of AI startups regularly sponsor H-1B and O-1 visas for ML engineers with strong research or production experience.
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Get Access To All JobsABOUT THE COMPANY
DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet.
ABOUT THE ROLE
The Foundation Model Team focuses on building large-scale foundation models for multi-agent behavior prediction and autonomous vehicle planning. By leveraging DiDi Voyager’s unparalleled driving data, we train highly robust and generalizable deep learning systems that enable safe and intelligent autonomous driving at scale.
Our models serve as the core intelligence of the autonomous driving stack, enabling vehicles to understand complex traffic scenarios, anticipate agent behavior, and make safe and efficient driving decisions.
We operate at the intersection of large-scale machine learning, autonomous driving, and foundation model research, pushing the frontier of multi-agent prediction and planning.
Responsibilities
As a member of the Foundation Model Team, you will:
-
Design and train large-scale deep learning models for:
-
Multi-agent trajectory prediction
-
Behavior and intent prediction
-
Planning and decision-making
-
Build foundation model architectures (Transformers, Diffusion, Flow-based models, Decision models, VLM/VLA)
-
Develop scalable training pipelines across hundreds to thousands of GPUs
-
Work with massive real-world datasets and build high-quality data pipelines
-
Optimize models for latency, reliability, and on-vehicle deployment
-
Collaborate closely with perception, mapping, simulation, and systems teams
-
Drive research ideas into production systems used by real autonomous vehicles
QUALIFICATIONS
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Strong background in machine learning, deep learning, or robotics
-
Experience with PyTorch / JAX / TensorFlow
-
Solid understanding of modern neural architectures (transformers, diffusion, auto-regressive)
-
Strong coding skills in Python and C++
-
Passion for building real-world, safety-critical AI systems
PREFERRED QUALIFICATIONS
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BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
-
Experience in autonomous driving, robotics, or embodied AI
-
Experience training large models on distributed GPU clusters
-
Experience with trajectory prediction, planning, or decision-making systems
-
Publications in top ML / robotics conferences (NeurIPS, ICML, ICLR, CVPR, RSS, CoRL, etc.)
COMPENSATION
- The base salary range for this position is $129,189-$247,038 annually in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa
ABOUT THE COMPANY
DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet.
ABOUT THE ROLE
The Foundation Model Team focuses on building large-scale foundation models for multi-agent behavior prediction and autonomous vehicle planning. By leveraging DiDi Voyager’s unparalleled driving data, we train highly robust and generalizable deep learning systems that enable safe and intelligent autonomous driving at scale.
Our models serve as the core intelligence of the autonomous driving stack, enabling vehicles to understand complex traffic scenarios, anticipate agent behavior, and make safe and efficient driving decisions.
We operate at the intersection of large-scale machine learning, autonomous driving, and foundation model research, pushing the frontier of multi-agent prediction and planning.
Responsibilities
As a member of the Foundation Model Team, you will:
-
Design and train large-scale deep learning models for:
-
Multi-agent trajectory prediction
-
Behavior and intent prediction
-
Planning and decision-making
-
Build foundation model architectures (Transformers, Diffusion, Flow-based models, Decision models, VLM/VLA)
-
Develop scalable training pipelines across hundreds to thousands of GPUs
-
Work with massive real-world datasets and build high-quality data pipelines
-
Optimize models for latency, reliability, and on-vehicle deployment
-
Collaborate closely with perception, mapping, simulation, and systems teams
-
Drive research ideas into production systems used by real autonomous vehicles
QUALIFICATIONS
-
Strong background in machine learning, deep learning, or robotics
-
Experience with PyTorch / JAX / TensorFlow
-
Solid understanding of modern neural architectures (transformers, diffusion, auto-regressive)
-
Strong coding skills in Python and C++
-
Passion for building real-world, safety-critical AI systems
PREFERRED QUALIFICATIONS
-
BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
-
Experience in autonomous driving, robotics, or embodied AI
-
Experience training large models on distributed GPU clusters
-
Experience with trajectory prediction, planning, or decision-making systems
-
Publications in top ML / robotics conferences (NeurIPS, ICML, ICLR, CVPR, RSS, CoRL, etc.)
COMPENSATION
- The base salary range for this position is $129,189-$247,038 annually in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on https://v.didi.cn/AQnxlBa
Machine Learning Engineer Job Roles in California
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Search Machine Learning Engineer Jobs in CaliforniaMachine Learning Engineer Jobs in California: Frequently Asked Questions
Which companies sponsor visas for machine learning engineers in California?
Large technology companies are the most consistent sponsors. Google, Meta, Apple, Amazon Web Services, Microsoft, and Nvidia all have significant California operations and established visa sponsorship programs for machine learning engineers. Beyond big tech, AI-focused companies like Anthropic, OpenAI, and Scale AI, as well as semiconductor and autonomous vehicle firms, regularly file H-1B petitions for ML roles in the state.
Which visa types are most common for machine learning engineer roles in California?
The H-1B is the most common visa category for machine learning engineers in California, given that ML roles typically require at least a bachelor's degree in computer science, mathematics, or a related field. Candidates with exceptional research records, publications, or competitive awards may qualify for the O-1A. Australians can pursue the E-3 as a lower-competition alternative for roles that meet specialty occupation requirements.
Which cities in California have the most machine learning engineer sponsorship jobs?
The San Francisco Bay Area, including San Jose, Mountain View, Menlo Park, and San Francisco itself, accounts for the largest share of ML engineering sponsorship roles in California. Los Angeles has a growing AI and entertainment-tech sector with active hiring. San Diego also sees demand from biotech, defense contractors, and research institutions like UC San Diego that feed into commercial ML roles.
How to find machine learning engineer visa sponsorship jobs in California?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to search for machine learning engineer roles in California without sorting through positions that do not sponsor. You can filter by location and role type to surface verified sponsoring employers across the Bay Area, Los Angeles, and San Diego. Creating a profile on Migrate Mate also helps match your background to relevant openings.
Are there any state-specific considerations for machine learning engineers seeking sponsorship in California?
California's concentration of H-1B-dependent employers means some companies must meet additional attestation requirements under DOL rules, which can affect hiring timelines. The state's university pipeline, particularly from Stanford, UC Berkeley, Caltech, and UCLA, creates significant competition for sponsored roles. ML engineers with specialized skills in large language models, computer vision, or MLOps tend to have stronger positioning with sponsors in the current California hiring market.
What is the prevailing wage for sponsored machine learning engineer jobs in California?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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