H-1B Visa Machine Learning Research Jobs
Machine Learning Research roles qualify as H-1B visa specialty occupations under the computer and mathematical sciences category, requiring at least a bachelor's degree in a directly related field. Employers filing H-1B petitions for these positions must certify a prevailing wage through DOL before USCIS adjudicates the petition.
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INTRODUCTION
It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.
We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.
The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.
The Future Forward organization is Intuitive’s advanced concepts group. We explore emerging technologies, prototype next-generation solutions, and build software experiences that shape the future of robotic-assisted surgery.
If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.
ROLE AND RESPONSIBILITIES
Primary Function of Position
We are building advanced augmented dexterity capabilities for next-generation robotic platforms. As a Senior AI/ML Research Engineer (Computer Vision), you will develop the perception models that let our Embodied-AI system understand the surgical scene. Working within a hierarchical, multimodal stack—where a high-level model interprets sensory observations into structured intent and a low-level policy turns that intent into precise, safe, real-time control—you will focus on the vision layer: designing, training, and evaluating models that extract anatomy, instruments, actions, and surgical context from intraoperative video. You will partner with the broader AI/ML team to define how perception feeds reasoning and control, and you will drive the research-to-deployment path for your models, taking them from offline experimentation to robust, real-time performance in the OR.
Working within Intuitive's Future Forward research organization, you will identify, build and finetune the AI/ML models and algorithms that enables us to deliver safe and performant embodied AI systems. This role calls for someone who is equally comfortable getting hands-on with models and data and designing systems that scale.
- Develop temporal models for activity and workflow understanding: event/state recognition and fine-grained temporal action segmentation.
- Benchmark in-house models against the state of the art and recommend the target perception architecture.
- Define the perception input/output specification and demonstrate offline feasibility on recorded data.
- Stand up a continuous-improvement loop (discrepancy flagging, active learning, human-in-the-loop relabeling) and the tooling/UI needed for offline evaluation and the path to real-time use.
- Partner with annotation and data teams to shape label taxonomies, QC, and the data pipeline that feeds the AI/ML models.
- Establish the path from offline evaluation on recorded data to real-time integration, including the continuous-improvement (human-in-the-loop) data loop.
- Partner with AI/ML researchers, robotics, data engineers, and other stakeholders to deliver a perception layer that enables rapid prototyping and learning while working toward a product solution.
MINIMUM QUALIFICATIONS
- MS or PhD in CS, EE, Robotics, or a related field, with 5+ years of applied computer-vision research experience.
- Strong grasp of modern CV and deep-learning fundamentals: CNNs and vision transformers, segmentation, detection, tracking, and representation/self-supervised learning.
- Demonstrated work in video understanding, including temporal action segmentation, action/phase recognition, and video segmentation.
- Hands-on experience with modern video architectures, including video transformers and self-supervised video pretraining.
- Exposure to vision-action (VA) / vision-language-action (VLA) models and world-model / self-supervised predictive architectures (e.g., JEPA-style models, MAE, DINO) for learning visual representations and dynamics.
- Experience working with large, messy, real-world video datasets at scale.
- Strong software and experimentation skills in Python and C++, with proficiency in one or more of PyTorch/TensorFlow/JAX, and the ability to stand up clean, reproducible experiments and run the full loop (data curation, augmentation, loss design, metrics, error analysis).
- A research-and-prototyping mindset: comfortable working in ambiguity, framing open-ended problems, running rapid experiments, and reading and reproducing recent papers to pull promising techniques into practice.
- Sound judgment about the path from prototype to product: writing code others can build on, knowing when to optimize versus when to move fast, and thinking ahead about data quality, evaluation, and robustness even at the research stage.
- Solid foundations in linear algebra, probability, and optimization, enough to reason about and debug model behavior from first principles.
- Comfort collaborating across a multidisciplinary team (ML, robotics, software, and clinical/domain experts) and communicating tradeoffs and findings clearly.
PREFERRED QUALIFICATIONS
- Background in healthcare, medical devices, surgical robotics, or other regulated technical domains.
- Sim-to-real workflows and experience with robotics simulators (e.g., NVIDIA Isaac).
- Experience with structured, ontology- or taxonomy-based labeling frameworks for fine-grained activity.
- Multimodal fusion of video with sensor, telemetry, and system-log streams.
- Designing annotation pipelines, QC processes, and active-learning loops.
- Real-time / edge inference optimization (e.g., TensorRT, NVIDIA Jetson).
- Fine-grained interaction and object-relationship modeling.
- Relevant peer-reviewed publications (CVPR, ICCV, ECCV, NeurIPS, etc.).
ADDITIONAL INFORMATION
Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role.
Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.
MANDATORY NOTICES
U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status.
Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process).
For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes.
We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.
Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.
This position may be filled at a different job level than listed here depending on business need and/or on the selected candidate’s experience, knowledge and skills.
Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law.
We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.
Base Compensation Range Region 1: $196,800 USD - $283,200 USD
Base Compensation Range Region 2: $167,300 USD - $240,700 USD
Shift: Day
Workplace Type: Onsite - This job is fully onsite.
LOCATION
Sunnyvale, CA, United States
Not Remote
JOB TYPE
Engineering
JOB216052
See all 439+ H-1B Visa Machine Learning Research Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship in Machine Learning Research
Verify your degree maps to the role
USCIS scrutinizes whether your degree field directly relates to machine learning research. A degree in computer science, statistics, or applied mathematics strengthens your petition. An unrelated degree, even with years of ML experience, increases RFE risk significantly.
Use OFLC Wage Search before negotiating salary
Pull the prevailing wage for your SOC code and work location using OFLC Wage Search before any offer discussion. Research roles often fall under Level III or IV wages, and knowing the floor prevents accepting an offer that fails DOL certification.
Target employers with cap-exempt H-1B filing history
Universities, nonprofit research institutions, and government research organizations can file H-1B petitions outside the annual cap. If you're pursuing a research role, these employers give you year-round petition filing without lottery exposure.
Search verified H-1B sponsors on Migrate Mate
Filter Machine Learning Research openings by employers with confirmed H-1B LCA filing history on Migrate Mate. This shows which companies have sponsored comparable roles, so you're not spending time on employers unlikely to file for your position.
Request premium processing before your OPT expires
If you're transitioning from OPT, file with premium processing so USCIS adjudicates within 15 business days. Standard processing can run several months, and an unadjudicated petition during a status gap creates authorization problems.
Confirm the job description covers specialty occupation
Ask your future employer to document that the Machine Learning Research role requires a specific technical degree, not just a generic bachelor's. Vague job descriptions that accept any STEM degree are the leading cause of specialty occupation RFEs.
H-1B Visa Machine Learning Research: Frequently Asked Questions
Does a Machine Learning Research role qualify as an H-1B specialty occupation?
Yes, provided the position requires a bachelor's degree or higher in a directly related field such as computer science, statistics, applied mathematics, or electrical engineering. USCIS evaluates the job duties, not the job title. If the role accepts any general degree, it may not meet the specialty occupation standard, which is why the job description's degree requirement language matters.
How do I find employers actively sponsoring H-1B visas for Machine Learning Research positions?
Search on Migrate Mate, which surfaces employers with verified H-1B LCA filing history for machine learning and research roles. DOL's LCA disclosure data is publicly available and shows which companies have filed for comparable positions, giving you a concrete shortlist rather than guessing at which employers are willing to sponsor.
What H-1B wage level typically applies to Machine Learning Research roles?
Most Machine Learning Research positions fall under SOC code 15-2051 (Data Scientists) or 15-1221 (Computer and Information Research Scientists). DOL assigns wage levels based on experience and supervisory responsibility. Entry-level researchers typically land at Level II, while senior or independent researchers often qualify at Level III or IV. Use OFLC Wage Search to verify the prevailing wage for your specific location.
Can I work on H-1B for a research university or national lab without entering the lottery?
Yes. Universities and affiliated nonprofit research organizations are cap-exempt H-1B employers, meaning they can file petitions at any time without competing in the annual lottery. National labs affiliated with universities or government agencies often share this exemption. Confirm the employer's cap-exempt status before assuming year-round filing is available, as the affiliation structure determines eligibility.
What documentation strengthens an H-1B petition for a Machine Learning Research role?
Your employer's petition benefits from a detailed job description tying specific duties to your degree field, academic transcripts showing relevant coursework, published research or conference papers demonstrating specialized expertise, and any professional certifications in relevant tools or methods. If your degree is from outside the U.S., a credential evaluation from a NACES-member evaluator showing equivalency to a U.S. bachelor's is essential for USCIS review.