H-1B Visa AI Research Engineer Jobs
AI Research Engineer roles sit firmly within H-1B visa specialty occupation requirements, typically demanding a master's or PhD in computer science, machine learning, or a closely related field. Employers filing H-1B petitions for these positions must certify a prevailing wage through a Labor Condition Application before USCIS can approve your petition.
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Get Access To All JobsINTRODUCTION
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The team is part of Google's Core ML organization. As a Staff AI Research Engineer, you will architect the strategy and roadmap for foundation recommender model pre-training. You will own the research agenda, defining and prioritizing experiments to drive continuous model quality within compute constraints. In this role, you will partner with data leads to shape collective roadmaps, ML infrastructure leads to define training framework requirements, and engagement teams to establish evaluation benchmarks.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
ROLE AND RESPONSIBILITIES
- Define and execute the long-term strategy for foundation recommender model pre-training, encompassing both model architecture evolution and future training methodologies.
- Drive a high-velocity research agenda focused on model quality, prioritizing experiments based on compute capacity and researcher bandwidth.
- Partner with ML infrastructure teams to architect training frameworks and ensure the technical ecosystem supports the research and release roadmap.
- Collaborate with data teams to plan data collection for pre-training, setting the standards for data quality to meet foundational model objectives.
- Establish evaluation benchmarks and maintain engaged leaderboards to track progress against baselines and ensure performance.
BASIC QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 2 years of experience in research, leading multiple research efforts and influencing research direction related to foundation models, Large Language Models, etc.
- Experience with transformer-based models (e.g., BERT, T5, GPT, ViT), attention mechanisms, and architectural variations.
PREFERRED QUALIFICATIONS
- Master’s degree or PhD in engineering, computer science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in an organization involving cross-functional or cross-business projects.
- Experience in publications (e.g., NeurIPS, ICML) or open-source contributions in RecSys, NLP, or multimodal systems.
COMPENSATION
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
INTRODUCTION
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The team is part of Google's Core ML organization. As a Staff AI Research Engineer, you will architect the strategy and roadmap for foundation recommender model pre-training. You will own the research agenda, defining and prioritizing experiments to drive continuous model quality within compute constraints. In this role, you will partner with data leads to shape collective roadmaps, ML infrastructure leads to define training framework requirements, and engagement teams to establish evaluation benchmarks.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
ROLE AND RESPONSIBILITIES
- Define and execute the long-term strategy for foundation recommender model pre-training, encompassing both model architecture evolution and future training methodologies.
- Drive a high-velocity research agenda focused on model quality, prioritizing experiments based on compute capacity and researcher bandwidth.
- Partner with ML infrastructure teams to architect training frameworks and ensure the technical ecosystem supports the research and release roadmap.
- Collaborate with data teams to plan data collection for pre-training, setting the standards for data quality to meet foundational model objectives.
- Establish evaluation benchmarks and maintain engaged leaderboards to track progress against baselines and ensure performance.
BASIC QUALIFICATIONS
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 2 years of experience in research, leading multiple research efforts and influencing research direction related to foundation models, Large Language Models, etc.
- Experience with transformer-based models (e.g., BERT, T5, GPT, ViT), attention mechanisms, and architectural variations.
PREFERRED QUALIFICATIONS
- Master’s degree or PhD in engineering, computer science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in an organization involving cross-functional or cross-business projects.
- Experience in publications (e.g., NeurIPS, ICML) or open-source contributions in RecSys, NLP, or multimodal systems.
COMPENSATION
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Research Engineer
Verify your SOC code before applying
AI Research Engineer roles often get classified under multiple SOC codes, which affects prevailing wage levels. Check O*NET to confirm which code matches your specific duties before your employer files the LCA, so there are no mismatches at adjudication.
Target cap-exempt employers strategically
Universities, nonprofit research organizations, and government-affiliated labs are cap-exempt, letting you skip the H-1B lottery entirely. If you're open to academic or applied research settings, these employers can file your petition at any point in the year.
Search verified H-1B sponsors on Migrate Mate
Filter by AI Research Engineer roles on Migrate Mate to find employers with confirmed H-1B filing history in your specialty. This saves time you'd otherwise spend cold-applying to companies that redirect research hires to contractors or don't sponsor directly.
Align your degree transcript to specialty occupation
USCIS scrutinizes AI Research Engineer petitions when degree fields are adjacent but not directly related. Have your employer's immigration counsel frame how your specific coursework, such as neural networks, probabilistic modeling, or systems design, maps to the role's duties in the I-129 petition.
Request premium processing before your start date
Standard H-1B processing can run four to six months. If your offer letter has a firm start date, ask your employer to file with premium processing so USCIS adjudicates within 15 business days and you're not waiting past your agreed onboarding timeline.
Confirm your employer's E-Verify enrollment
If you're on STEM OPT and transitioning to H-1B, your employer must already be enrolled in E-Verify for your OPT extension to remain valid. Confirm enrollment before accepting an offer, not after, to avoid a gap in work authorization.
H-1B Visa AI Research Engineer: Frequently Asked Questions
Does an AI Research Engineer role qualify as a specialty occupation for H-1B purposes?
Yes. USCIS classifies AI Research Engineer positions as specialty occupations because they normally require at least a bachelor's degree in a directly related field such as computer science, electrical engineering, or applied mathematics. Roles focused on model development, algorithm design, or systems research generally clear this threshold without additional justification, though USCIS may issue an RFE if the position description is broad or the degree field is tangentially related.
How do I find employers who actively sponsor H-1B visas for AI research roles?
Use Migrate Mate to browse AI Research Engineer positions filtered by employers with verified H-1B filing history. DOL Labor Condition Application data is publicly available and shows which companies have filed for comparable roles, giving you a concrete signal of sponsorship intent before you apply rather than discovering a company's policy after an offer.
What happens to my H-1B status if my AI research project is defunded mid-petition?
If your employer withdraws the H-1B petition before USCIS approves it, the petition is terminated and you'll need a new employer to file on your behalf. If you're already in valid H-1B status and your position is eliminated, you have a 60-day grace period to find a new employer, transfer your H-1B, or depart the U.S. USCIS does not extend this window for project-based cancellations.
Can an AI Research Engineer role at a startup qualify for H-1B sponsorship?
Yes, but startups face additional scrutiny. USCIS may issue an RFE requesting evidence that the employer has sufficient work and financial capacity to maintain the position for the full petition period. Your employer should document the research scope, funding sources, and organizational structure alongside the I-129. Early-stage companies with substantial venture backing or government research contracts typically satisfy this requirement.
Does holding a PhD in machine learning improve my H-1B approval odds for an AI Research Engineer position?
A PhD strengthens the specialty occupation argument because it directly demonstrates the theoretical depth the role requires. USCIS evaluates whether the position itself requires advanced study, not just whether you hold a higher degree. For senior or principal research engineer roles, a PhD can also support a higher Level III or IV prevailing wage classification under the OFLC Wage Search, which your employer must certify in the Labor Condition Application.