H-1B Visa ML Research Engineer Jobs
ML Research Engineer roles qualify as H-1B visa specialty occupations under the computer and mathematical sciences category, requiring at least a bachelor's degree in computer science, machine learning, or a directly related field. Most research-focused positions at labs and tech companies have active H-1B filing histories, making this one of the more sponsorship-accessible paths for international candidates.
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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
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a ML Research Engineer
Frame your research portfolio for specialty occupation
USCIS evaluates whether your role requires a specific theoretical body of knowledge. Document how your ML research draws on advanced mathematics, statistics, or computer science, not just engineering execution. Peer-reviewed publications and patent filings strengthen this directly.
Check LCA filings before applying
Use Migrate Mate to filter employers by verified H-1B Labor Condition Application history in ML and research roles. This surfaces companies that have already cleared DOL prevailing-wage certification for positions matching your target job code, not just companies that sponsor in general.
Target cap-exempt employers strategically
Universities, nonprofit research institutions, and certain government-affiliated labs are exempt from the annual H-1B cap and lottery. If your research background fits academic or applied science contexts, these employers can file for you any time of year without a registration slot.
Verify your wage tier before negotiating an offer
Your employer's LCA must certify your salary at the DOL prevailing wage for your SOC code and work location. Look up the wage level for ML Research Engineer roles in your target metro using the OFLC Wage Search before accepting an offer, so you know the floor your employer must meet.
Request premium processing if your start date is tight
USCIS offers premium processing for H-1B petitions, reducing adjudication to 15 business days. For ML Research Engineer roles starting after an OPT expiration or mid-year transition, confirm with your employer that they'll request it, standard processing can run five to seven months.
Align your job description to your O*NET profile
The O*NET profile for ML Research Engineer roles lists specific knowledge domains and skill requirements USCIS reviewers reference during specialty occupation adjudication. Ask your employer to ensure the job description mirrors this language to reduce the risk of a Request for Evidence.
H-1B Visa ML Research Engineer: Frequently Asked Questions
Does an ML Research Engineer role qualify as an H-1B specialty occupation?
Yes. ML Research Engineer positions fall under the computer and mathematical sciences occupational category, which USCIS consistently recognizes as a specialty occupation. The role must require at least a bachelor's degree in a directly related field such as computer science, machine learning, statistics, or applied mathematics. Roles that accept any degree or treat the degree requirement as a preference rather than a requirement can face challenges during adjudication.
Which types of employers sponsor H-1B visas for ML Research Engineer roles?
Large technology companies, AI-focused startups, national laboratories, and research universities are the most active sponsors for ML Research Engineer positions. Universities and nonprofit research institutions are cap-exempt, meaning they can file H-1B petitions outside the lottery window. You can browse employers with verified H-1B filing history for research and ML roles on Migrate Mate, filtered by location and job function.
How does the H-1B lottery affect ML Research Engineer job seekers?
The annual H-1B cap covers most private-sector employers, with registrations typically open in March for an October 1 start date. USCIS selects registrations by random lottery when demand exceeds the 85,000 available slots. If you're targeting cap-exempt employers like universities or federally funded research labs, the lottery doesn't apply and your employer can file any time your position is ready.
What documents should I prepare before an employer files my H-1B petition?
You'll need your highest academic credentials with translations if applicable, your current immigration status documents, and a detailed resume aligned to the specialty occupation definition. For ML Research Engineer roles, supporting evidence such as published research, conference proceedings, or patents helps establish that your position requires specialized theoretical knowledge. Your employer's attorney typically compiles the petition, but your documentation package directly affects adjudication speed.
Can I switch ML Research Engineer employers after my H-1B is approved?
Yes, under H-1B portability rules established by AC21, you can transfer your H-1B to a new employer once your petition has been pending or approved for at least 180 days, provided the new role is in the same or a similar occupational classification. Your new employer files an H-1B transfer petition and you can begin work once they receive the receipt notice, without waiting for final approval.