AI Research Engineer Visa Sponsorship Jobs in California
California is the top state for AI research engineer visa sponsorship jobs, with major employers including Google DeepMind, Meta AI, Apple, and OpenAI concentrated across the San Francisco Bay Area, Silicon Valley, and San Diego. The state's density of AI labs, research universities, and deep-pocketed tech employers makes it the most active market for sponsored roles in this field.
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Get Access To All JobsWe are so glad you are interested in joining Sutter Health!
Organization
SHSO-Sutter Health System Office-Valley
Position Overview
Leads Sutter Health's artificial intelligence (AI) governance program. Sets the target operating model, policy framework, and program priorities that shape how AI governance is performed at Sutter Health and how it evolves within a rapidly changing regulatory, technical, and organizational landscape. Leads a team of AI governance analysts and operates the program directly alongside them — leading high-complexity reviews, drafting policy and standards, and making day-to-day prioritization decisions across a high-volume queue of AI use cases. Convenes and aligns the many groups that must participate in AI governance and partners closely with data science and applied AI leadership to integrate governance requirements across the model development and monitoring lifecycle.
Education
Equivalent experience will be accepted in lieu of the required degree or diploma.
* Bachelor's degree in Health Informatics, Computer Science, Information Management, Public Health, Health Administration, Law, or related field.
Typical Experience
* 5 recent relevant experience
Skills And Knowledge
Experience in healthcare data governance, AI/ML governance, model risk management, or regulatory compliance.
Experience leading or coordinating cross-functional governance, risk, or compliance programs.
Direct experience supporting AI/ML or advanced analytics programs.
Strong organization and prioritization skills across a large, varied portfolio of work and competing demands.
Demonstrated ability to convene, align, and drive decisions among diverse stakeholder groups, including clinical, technical, legal, privacy, security, compliance, and operational.
Working knowledge of machine learning and generative AI concepts, the model development lifecycle, and common failure modes (bias, drift, hallucination, data leakage).
Possess an understanding of technical concepts related to AI observability, including performance instrumentation for deployed models; familiarity with advanced monitoring techniques such as Large Language Model (LLM)-as-a-judge evaluation, automated output quality assessment, and monitoring of agentic AI workflows, including tool use, multi-step reasoning, and autonomous decision chains.
Familiarity with AI governance frameworks (National Institute of Standards and Technology Artificial Intelligence Risk Management Framework [NIST AI RMF], Coalition for Health AI [CHAI] Assurance Standards, International Organization for Standardization/International Electrotechnical Commission [ISO/IEC] 42001), healthcare regulations (Health Insurance Portability and Accountability Act [HIPAA], Food and Drug Administration [FDA] Software as a Medical Device [SaMD] guidance, Office of the National Coordinator for Health Information Technology [ONC] Health Data, Technology, and Interoperability [HTI-1] rule), and emerging state-level AI regulation.
Demonstrated ability to design and operate governance processes that are practical, auditable, and minimize friction for delivery teams.
Strong facilitation and written communication; able to lead committees and translate complex AI risk concepts for executive, clinical, and front-line audiences.
Demonstrated ability to manage team capacity, prioritization, and delivery across a high-volume, multi-stakeholder portfolio.
Experience coaching and developing staff in both technical and governance/regulatory domains.
These Principal Accountabilities, Requirements and Qualifications are not exhaustive but are merely the most descriptive of the current job. Management reserves the right to revise the job description or require that other tasks be performed when the circumstances of the job change (for example, emergencies, staff changes, workload, or technical development).
Job Shift
Days
Schedule
Full Time
Days Of The Week
Monday - Friday
Weekend Requirements
None
Benefits
Yes
Unions
No
Position Status
Exempt
Weekly Hours
40
Employee Status
Regular
Sutter Health is an equal opportunity employer EOE/M/F/Disability/Veterans.
Pay Range is $156,332.80 to $234,478.40 / annual salary
The compensation range may vary based on the geographic location where the position is filled. Total compensation considers multiple factors, including, but not limited to a candidate’s experience, education, skills, licensure, certifications, departmental equity, training, and organizational needs. Base pay is only one component of Sutter Health’s comprehensive total rewards program. Eligible positions also include a comprehensive benefits package.
We are so glad you are interested in joining Sutter Health!
Organization
SHSO-Sutter Health System Office-Valley
Position Overview
Leads Sutter Health's artificial intelligence (AI) governance program. Sets the target operating model, policy framework, and program priorities that shape how AI governance is performed at Sutter Health and how it evolves within a rapidly changing regulatory, technical, and organizational landscape. Leads a team of AI governance analysts and operates the program directly alongside them — leading high-complexity reviews, drafting policy and standards, and making day-to-day prioritization decisions across a high-volume queue of AI use cases. Convenes and aligns the many groups that must participate in AI governance and partners closely with data science and applied AI leadership to integrate governance requirements across the model development and monitoring lifecycle.
Education
Equivalent experience will be accepted in lieu of the required degree or diploma.
* Bachelor's degree in Health Informatics, Computer Science, Information Management, Public Health, Health Administration, Law, or related field.
Typical Experience
* 5 recent relevant experience
Skills And Knowledge
Experience in healthcare data governance, AI/ML governance, model risk management, or regulatory compliance.
Experience leading or coordinating cross-functional governance, risk, or compliance programs.
Direct experience supporting AI/ML or advanced analytics programs.
Strong organization and prioritization skills across a large, varied portfolio of work and competing demands.
Demonstrated ability to convene, align, and drive decisions among diverse stakeholder groups, including clinical, technical, legal, privacy, security, compliance, and operational.
Working knowledge of machine learning and generative AI concepts, the model development lifecycle, and common failure modes (bias, drift, hallucination, data leakage).
Possess an understanding of technical concepts related to AI observability, including performance instrumentation for deployed models; familiarity with advanced monitoring techniques such as Large Language Model (LLM)-as-a-judge evaluation, automated output quality assessment, and monitoring of agentic AI workflows, including tool use, multi-step reasoning, and autonomous decision chains.
Familiarity with AI governance frameworks (National Institute of Standards and Technology Artificial Intelligence Risk Management Framework [NIST AI RMF], Coalition for Health AI [CHAI] Assurance Standards, International Organization for Standardization/International Electrotechnical Commission [ISO/IEC] 42001), healthcare regulations (Health Insurance Portability and Accountability Act [HIPAA], Food and Drug Administration [FDA] Software as a Medical Device [SaMD] guidance, Office of the National Coordinator for Health Information Technology [ONC] Health Data, Technology, and Interoperability [HTI-1] rule), and emerging state-level AI regulation.
Demonstrated ability to design and operate governance processes that are practical, auditable, and minimize friction for delivery teams.
Strong facilitation and written communication; able to lead committees and translate complex AI risk concepts for executive, clinical, and front-line audiences.
Demonstrated ability to manage team capacity, prioritization, and delivery across a high-volume, multi-stakeholder portfolio.
Experience coaching and developing staff in both technical and governance/regulatory domains.
These Principal Accountabilities, Requirements and Qualifications are not exhaustive but are merely the most descriptive of the current job. Management reserves the right to revise the job description or require that other tasks be performed when the circumstances of the job change (for example, emergencies, staff changes, workload, or technical development).
Job Shift
Days
Schedule
Full Time
Days Of The Week
Monday - Friday
Weekend Requirements
None
Benefits
Yes
Unions
No
Position Status
Exempt
Weekly Hours
40
Employee Status
Regular
Sutter Health is an equal opportunity employer EOE/M/F/Disability/Veterans.
Pay Range is $156,332.80 to $234,478.40 / annual salary
The compensation range may vary based on the geographic location where the position is filled. Total compensation considers multiple factors, including, but not limited to a candidate’s experience, education, skills, licensure, certifications, departmental equity, training, and organizational needs. Base pay is only one component of Sutter Health’s comprehensive total rewards program. Eligible positions also include a comprehensive benefits package.
AI Research Engineer Job Roles in California
See all 6,213+ AI Research Engineer Jobs in California
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Search AI Research Engineer Jobs in CaliforniaAI Research Engineer Jobs in California: Frequently Asked Questions
Which companies sponsor visas for AI research engineers in California?
The most active sponsors for AI research engineer roles in California include Google DeepMind, Meta AI Research, Apple, Microsoft Research, Amazon, NVIDIA, and OpenAI, all of which have significant research operations in the Bay Area or Los Angeles. Many also maintain dedicated research labs staffed largely by PhD-level engineers on H-1B visa or O-1 visas, and their sponsorship history is publicly documented in DOL LCA disclosure data.
Which visa types are most common for AI research engineer roles in California?
The H-1B is the most common visa for AI research engineers in California, as these roles typically require a bachelor's degree or higher in computer science, machine learning, or a related field, meeting the specialty occupation standard. Candidates with exceptional publication records or awards may qualify for the O-1A. Those with U.S. master's or PhD degrees from California universities may also enter through OPT before transitioning to H-1B sponsorship.
How to find ai research engineer visa sponsorship jobs in California?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search AI research engineer roles in California without sorting through positions that don't sponsor. The platform surfaces openings at companies with verified sponsorship history, which is particularly useful in California given the volume of AI roles that list advanced degree requirements. Start your search on Migrate Mate and filter by state to narrow results to California employers.
Which cities in California have the most AI research engineer sponsorship jobs?
The San Francisco Bay Area, including San Jose, Mountain View, Menlo Park, and San Francisco itself, accounts for the largest concentration of AI research engineer sponsorship jobs in California by a wide margin. Los Angeles is a growing secondary market, driven by companies like Google, Snap, and a cluster of AI startups. San Diego also has a notable presence through Qualcomm AI Research and biotech-adjacent AI roles.
Are there any California-specific considerations for AI research engineers seeking visa sponsorship?
California's prevailing wage requirements under DOL rules apply to H-1B LCA filings, and the Bay Area is designated as a high-cost metropolitan area, which means the prevailing wage floor for AI research engineer roles is among the highest in the country. California also has strict employee classification laws, which means most sponsored AI research positions are direct employment roles rather than contractor arrangements. The state's concentration of top-ranked CS programs at UC Berkeley, Stanford, and UCLA creates a strong local pipeline that employers actively recruit from.
What is the prevailing wage for sponsored ai research 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.