H-1B1 Chile Visa Machine Learning Engineer Jobs
Machine Learning Engineer roles qualify for H-1B1 Chile visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, engineering, or a related field. Chilean nationals skip the H-1B lottery entirely, with the 1,400-visa annual cap rarely exhausted and applications handled directly at the consulate.
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Company Description
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.
If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.
Job Description
Primary Function
The AI Research group within Intuitive Surgical has an immediate opening in Sunnyvale, CA for a Machine Learning Engineer with focus on physical AI systems, robotics simulation environments and end-to-end ML pipelines, contributing to new technology development for next-generation robot-assisted surgery platforms.
Key Responsibilities
- Design, implement, and optimize scalable Simulation and RL infrastructure for training surgical robots in simulated environments, leveraging distributed systems for parallel processing and high-throughput simulations
- Optimize performance across the simulation stack, including distributed systems, Inference, and rendering, to ensure optimal usage of hardware resources and fast, efficient simulations
- Sim-to-Real Validation: Support efforts to reduce the sim-to-real gap through domain randomization, noise modelling, and physics-based constraints.
- Synthetic Data Generation: Develop simulation workflows to produce synthetic datasets for AI model training and validation.
- Designing large-scale data pipelines from multimodal robot sensor streams (vision, depth, proprioception, action logs)
- Running structured experimentation across architectures, datasets, and training strategies for physical AI systems
- Contribute to end-to-end learning pipelines from data collection training evaluation to real-world deployment
- Work with AI/ML engineers to integrate simulation outputs into training pipelines, especially for physics-informed models.
- Deliver high-quality, production-ready code in a dynamic and fast-paced environment
- Contribute to building new clinical datasets and data pipelines.
- Participate in integration of new ML/CV algorithms into existing and future robotic platforms.
- Collaborate with users and clinical advisors to iterate prototype designs based on feedback and performance.
Qualifications
Experience and Abilities
- Doctoral degree in computer science, electrical and computer engineering, or Master's degree with minimum (5) years industry experience developing robotics and machine learning applications.
- Strong background in ML infrastructure, including designing training pipelines, data orchestration, and deployment of RL models at scale
- Proficiency in GPU optimizations for either inference or rendering
- Proficiency in Python, with familiarity in frameworks like PyTorch, TensorFlow, or RL libraries, and a proven ability to write clean, scalable, and efficient code
- Ability to research, implement, and adapt cutting-edge techniques from academic and industry sources into practical, production-ready solutions for scalable RL in simulation
- Strong hands-on experience with Python (proficiency), C/C++ (proficiency), shell scripting
- Excellent communication skills both written and verbal.
- Self-starter and able to work in a collaborative and results-oriented environment.
- Ability to travel domestically and internationally (5-15%)
- Able to view live and recorded surgical procedures.
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: $164,000 USD - $236,000 USD
Base Compensation Range Region 2: $139,400 USD - $200,600 USD
Shift: Day
Workplace Type: Onsite - This job is fully onsite.
Location: San Francisco, CA, United States
Job Type: Not Remote
Department: Engineering
Job ID: JOB216388
See all 143+ H-1B1 Chile Visa Machine Learning Engineer Jobs
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Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Engineer
Verify your degree maps to the role
Consular officers assess whether your bachelor's degree field directly relates to machine learning engineering. A degree in computer science, mathematics, or electrical engineering clears the bar. Statistics or physics degrees may need supporting coursework documentation to establish the connection.
Target employers with active LCA filing history
Search the OFLC Wage Search to confirm a company has previously filed Labor Condition Applications for machine learning or software engineering roles. Employers already familiar with LCA certification are far less likely to stall when you raise H-1B1 Chile sponsorship in negotiations.
Use Migrate Mate to surface H-1B1 Chile employers
Filter your job search on Migrate Mate to find employers with documented H-1B1 Chile filing history for machine learning and engineering roles, so you're spending time on companies that have already worked through the sponsorship process rather than educating employers from scratch.
Benchmark your offer against DOL prevailing wage
Before signing an offer, run your job title and location through the OFLC Wage Search to confirm the offered salary meets the DOL prevailing wage for your wage level. An LCA will be rejected if the offered wage falls below the certified threshold, which delays your consular appointment.
Clarify the LCA timeline before accepting an offer
Ask the employer specifically how long DOL LCA certification typically takes on their end. Standard certification runs about seven business days, but employers filing for the first time may need additional lead time to register in the FLAG system and prepare supporting documentation.
Pull your O*NET occupation profile before interviews
Review the O*NET profile for Machine Learning Engineer or the closest matching occupation to understand the official degree requirements and job duties the consular officer will reference. Framing your experience using language aligned with O*NET strengthens your specialty occupation argument during the interview.
Frequently Asked Questions
Does a machine learning engineer role qualify as a specialty occupation for the H-1B1 Chile visa?
Yes. Machine learning engineering requires at least a bachelor's degree in computer science, mathematics, engineering, or a closely related field, which satisfies the specialty occupation definition. You'll want to ensure your offer letter and any employer documentation describe duties that require that theoretical and practical application of those disciplines, not just general software development tasks.
How does the H-1B1 Chile visa differ from H-1B for machine learning engineers?
The H-1B1 Chile visa has no lottery, a dedicated annual cap of 1,400 for Chilean nationals that rarely fills, and is processed at the consulate rather than through USCIS petition. You don't need an I-129 petition, which removes several months of waiting. The trade-off is that the H-1B1 does not allow dual intent, so you cannot simultaneously pursue a green card while on H-1B1 status.
Can I find machine learning engineer employers who sponsor H-1B1 Chile visas through Migrate Mate?
Yes. Migrate Mate lets you filter specifically for employers with H-1B1 Chile filing history in engineering and machine learning roles, so you're targeting companies that have already worked through the LCA and consular process rather than approaching employers who have no experience with this visa category.
What does the employer actually file for an H-1B1 Chile visa sponsorship?
The employer files a Labor Condition Application with the DOL through the FLAG system. DOL must certify the LCA, which typically takes about seven business days. Once certified, you take that LCA along with your job offer and supporting credentials to your consular interview. There's no USCIS petition stage, which is the key procedural difference from the H-1B process.
Can I renew my H-1B1 Chile visa if my machine learning engineering project extends beyond the initial period?
H-1B1 Chile status is granted in one-year increments and can be renewed indefinitely as long as you maintain a qualifying job offer and your employer files a new certified LCA for each renewal period. There's no statutory maximum on renewals, so long-term employment at the same company is straightforward provided the role continues to meet specialty occupation requirements.