ML Research Engineer Jobs in USA with Visa Sponsorship
ML Research Engineer roles attract strong H-1B visa sponsorship from AI labs, large tech companies, and research-focused startups. A master's or PhD in computer science or a related field is standard, and employers regularly sponsor both new graduates and experienced researchers. For detailed occupation requirements, see the O*NET profile.
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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 Visa Sponsorship as a ML Research Engineer
Target employers with established research divisions
AI labs and large tech companies with dedicated research teams sponsor H-1B petitions far more consistently than startups without legal infrastructure. Look for organizations with a track record of LCA filings under ML-related job titles.
Lead with publications and research output
Sponsoring employers want evidence of original contribution. A strong publication record at NeurIPS, ICML, or ICLR signals exactly the kind of specialized expertise USCIS expects to see supporting an H-1B specialty occupation claim.
Understand how your degree field maps to the role
USCIS requires a direct relationship between your degree field and the position. Computer science, electrical engineering, statistics, and applied mathematics are the most defensible degree fields for ML Research Engineer sponsorship petitions.
PhD candidates have a meaningful advantage at research-focused employers
Many AI labs require a doctorate for research-track roles. A PhD also strengthens the specialty occupation argument in an H-1B petition and can support an EB-1A or EB-2 NIW green card filing later.
Ask about premium processing during your offer negotiation
USCIS premium processing reduces the H-1B petition review window to 15 business days. Research-focused employers routinely pay this fee, and it is a reasonable expectation to raise during the offer discussion stage.
Know your OPT and STEM OPT timeline before accepting an offer
STEM OPT gives you 36 months of post-graduation work authorization. Aligning your H-1B filing with the April cap season during that window ensures continuous work authorization without any gap in employment.
Frequently Asked Questions
Do ML Research Engineer roles qualify as H-1B specialty occupations?
Yes. ML Research Engineering consistently qualifies as a specialty occupation because the role requires at minimum a bachelor's degree in a specific technical field, such as computer science, statistics, or electrical engineering. Employers at AI labs and major tech companies have a strong track record of approved H-1B visa petitions for this title, and the position's theoretical depth reinforces the specialty occupation argument.
Is a PhD required to get H-1B sponsorship as an ML Research Engineer?
Not always, but it depends heavily on the employer and the seniority of the role. Research-track positions at dedicated AI labs frequently require a PhD as a minimum qualification, which actually strengthens the specialty occupation case for H-1B purposes. Applied or production-focused ML Research Engineer roles at larger tech companies may sponsor candidates with a strong master's degree and relevant publications or industry experience.
How does the H-1B lottery affect ML Research Engineers specifically?
ML Research Engineers face the same general-category lottery odds as most other H-1B applicants, with a selection rate around 25% in recent years. However, researchers with a U.S. master's or PhD from a U.S. institution enter the advanced degree pool first, which has historically offered slightly better odds. Employers at universities and nonprofit research institutions are cap-exempt, meaning those roles bypass the lottery entirely.
Can an ML Research Engineer self-petition for a green card without employer sponsorship?
Yes, the EB-2 National Interest Waiver is the most viable self-petition path for ML researchers. USCIS has granted NIW approval to researchers demonstrating that their work has national importance and that they are well-positioned to advance it. A strong publication record, citations, and evidence of impact on the field significantly improve approval odds. Some exceptional researchers also qualify for the EB-1A extraordinary ability category.
Where can I find ML Research Engineer jobs that offer visa sponsorship?
Migrate Mate is built specifically for international candidates and filters for roles where employers are open to sponsoring work visas. Browsing ML Research Engineer listings on Migrate Mate lets you focus on employers with verified sponsorship histories rather than sorting through postings that exclude international applicants. It is the most direct way to find research roles aligned with your visa situation.
What is the prevailing wage requirement for sponsored ML Research Engineer jobs?
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.