Green Card Machine Learning Jobs
Machine learning roles sit squarely within EB-2 and EB-3 specialty occupation categories, making them strong candidates for PERM-based green card sponsorship. Employers file a labor certification with DOL before petitioning USCIS, permanently tying your residency to a qualifying ML position rather than a temporary work authorization cycle.
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Job Description: Our Mission At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people—powerful in capability, yet honest about its limits and protective of the data and resources it touches. To get there, we build agentic AI that combines the best of local and cloud intelligence — private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise—data stays private, spend stays predictable, and energy use stays in check. We're building intelligence that scales without sacrificing trust, cost, or the planet—because the future of AI should belong to the people it serves.
Role Summary We are seeking a Machine Learning Engineer / Data Scientist to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal candidate designs and implements algorithms for agent harness and post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications.
What you’ll do
Work In a Dynamic Team To
- Build evaluation benchmarks and metrics
- Build and iterate on agent harness, including context engineering, agent memory, tools, skills.
- Build, maintain, and iterate on the post-training pipeline: Develop robust, reproducible training workflows from data ingestion and preprocessing through model checkpointing and deployment
- Design RL environments and reward functions — Develop environments, reward signals, and verifiable reward frameworks for training models on reasoning-intensive tasks.
- Debug and optimize training runs — Profile training jobs, resolve bottlenecks, improve GPU utilization, and address numerical instability at multi-GPU scale
What you’ll learn / grow into
Curiosity Is Required. You Will Develop
- How post-training techniques actually move model performance
- How to make small models punch above their weight as agent backends
- How model choices interact with runtime constraints on edge hardware
Qualifications
Required Qualifications
- BS in CS, EE, Math or related STEM field
- 5+ years software development background
- 2+ years of hands-on experience in machine learning engineering, data science or ML research
- Proficient in Python
- Proficient in LLM architectures, optimization and model training dynamics.
Preferred Qualifications
- Masters or PhD degrees are preferred.
- Hands-on experience implementing and scaling the full post-training pipeline for language models including supervised fine tuning and reinforcement learning.
- Previous experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality
- Ability to own and drive a research agenda independently, generating hypotheses and prioritizing experiments without step-by-step supervision.
- Ambiguity tolerance: Comfortable making progress in fast-moving environments where problem definitions evolve and priorities shift.
- Debug-first mindset: Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle issues.
- Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.
- Collaborative work style: Comfort with cross-functional collaboration.
- Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.
- Ability to learn new technologies fast and adapt to changes with open-mindedness.
Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.
Benefits At Intel
Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Go to Intel Benefits | Intel Careers for details of benefits available to you. Intel reserves the right to modify, change or discontinue benefit plans at any time in its sole discretion.
Shift
Job Type: Shift 1 (United States of America)
Primary Location: US, California, Santa Clara
Additional Locations: US, Arizona, Phoenix, US, California, Folsom, US, Oregon, Hillsboro
Business Group
The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them.
Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust N/A
Benefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $170,500.00 - 315,490.00 USD
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. 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 compensation range for your preferred location during the hiring process.
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site.
- Job posting details (such as work model, location or time type) are subject to change.
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.
Job Details
Job Description: Our Mission At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people—powerful in capability, yet honest about its limits and protective of the data and resources it touches. To get there, we build agentic AI that combines the best of local and cloud intelligence — private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise—data stays private, spend stays predictable, and energy use stays in check. We're building intelligence that scales without sacrificing trust, cost, or the planet—because the future of AI should belong to the people it serves.
Role Summary We are seeking a Machine Learning Engineer / Data Scientist to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal candidate designs and implements algorithms for agent harness and post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications.
What you’ll do
Work In a Dynamic Team To
- Build evaluation benchmarks and metrics
- Build and iterate on agent harness, including context engineering, agent memory, tools, skills.
- Build, maintain, and iterate on the post-training pipeline: Develop robust, reproducible training workflows from data ingestion and preprocessing through model checkpointing and deployment
- Design RL environments and reward functions — Develop environments, reward signals, and verifiable reward frameworks for training models on reasoning-intensive tasks.
- Debug and optimize training runs — Profile training jobs, resolve bottlenecks, improve GPU utilization, and address numerical instability at multi-GPU scale
What you’ll learn / grow into
Curiosity Is Required. You Will Develop
- How post-training techniques actually move model performance
- How to make small models punch above their weight as agent backends
- How model choices interact with runtime constraints on edge hardware
Qualifications
Required Qualifications
- BS in CS, EE, Math or related STEM field
- 5+ years software development background
- 2+ years of hands-on experience in machine learning engineering, data science or ML research
- Proficient in Python
- Proficient in LLM architectures, optimization and model training dynamics.
Preferred Qualifications
- Masters or PhD degrees are preferred.
- Hands-on experience implementing and scaling the full post-training pipeline for language models including supervised fine tuning and reinforcement learning.
- Previous experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality
- Ability to own and drive a research agenda independently, generating hypotheses and prioritizing experiments without step-by-step supervision.
- Ambiguity tolerance: Comfortable making progress in fast-moving environments where problem definitions evolve and priorities shift.
- Debug-first mindset: Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle issues.
- Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.
- Collaborative work style: Comfort with cross-functional collaboration.
- Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.
- Ability to learn new technologies fast and adapt to changes with open-mindedness.
Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.
Benefits At Intel
Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Go to Intel Benefits | Intel Careers for details of benefits available to you. Intel reserves the right to modify, change or discontinue benefit plans at any time in its sole discretion.
Shift
Job Type: Shift 1 (United States of America)
Primary Location: US, California, Santa Clara
Additional Locations: US, Arizona, Phoenix, US, California, Folsom, US, Oregon, Hillsboro
Business Group
The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them.
Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust N/A
Benefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $170,500.00 - 315,490.00 USD
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. 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 compensation range for your preferred location during the hiring process.
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site.
- Job posting details (such as work model, location or time type) are subject to change.
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.
See all 3,758+ Green Card Machine Learning Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Green Card Machine Learning Jobs.
Get Access To All JobsTips for Finding Green Card Sponsorship in Machine Learning
Frame your ML credentials for PERM documentation
PERM requires your employer to prove the role genuinely needs a degree in a specific field. Gather transcripts, publications, and project portfolios that show your machine learning specialization maps directly to the advertised job duties, not just general software engineering.
Target employers with active PERM filing history
Not every tech employer sponsors green cards, even if they hire on H-1B visa. Search DOL PERM disclosure data to identify companies that have filed labor certifications for ML-specific job titles like 'Machine Learning Engineer' or 'Research Scientist' in the past two years.
Search green card jobs on Migrate Mate
Migrate Mate filters job listings specifically by green card sponsorship history, so you're not guessing which ML employers will file PERM. Use it to surface roles where sponsorship is already part of the hiring process, not an afterthought you negotiate later.
Distinguish EB-2 NIW from employer-sponsored EB-2
If your ML research has national-scale impact, a National Interest Waiver lets you self-petition under EB-2 without a PERM labor certification. Published models, patents, or government-funded research often support NIW eligibility, bypassing the employer-driven recruitment advertising timeline entirely.
Negotiate PERM filing timing before signing an offer
Ask prospective employers whether they will file PERM within your first year, since the Department of Labor recruitment and audit process adds 12 to 18 months before USCIS even sees your I-140. Clarifying this in the offer stage prevents multi-year delays after you've already started.
Verify your ML job title matches DOL wage-level categories
PERM prevailing wages are calculated against specific SOC codes. 'Machine Learning Engineer' and 'Data Scientist' map to different O*NET profiles with different wage levels. Confirm with your employer which SOC code they plan to use via OFLC Wage Search before the labor certification is filed.
Green Card Machine Learning: Frequently Asked Questions
Do machine learning roles qualify for EB-2 or EB-3 green card sponsorship?
Most machine learning positions qualify under EB-2 because they typically require an advanced degree in computer science, statistics, or a related field and involve work that cannot be performed by someone without that specialized education. Roles at the entry or mid-level that require only a bachelor's degree may fall under EB-3 instead. Your employer's attorney will determine the correct category based on the actual job requirements, not your personal credentials.
How does green card sponsorship differ from H-1B for ML engineers?
H-1B is a temporary work visa capped at 85,000 new slots annually and subject to a lottery. Green card sponsorship through PERM and I-140 is permanent residency with no annual cap at the EB-3 level for most countries outside India and China. The PERM process takes longer up front, often 18 to 24 months from labor certification to I-140 approval, but the outcome is lawful permanent residency rather than a renewable temporary status.
Where can I find machine learning jobs that offer green card sponsorship?
Migrate Mate is built specifically for this search. It surfaces ML job listings filtered by employers with documented green card sponsorship history, so you can focus your applications on companies that have already filed PERM labor certifications for similar roles rather than cold-applying and asking later whether sponsorship is available.
What does the PERM labor certification process require from my employer?
Your employer must conduct a DOL-supervised recruitment campaign to demonstrate that no qualified U.S. worker is available for the role. For ML positions, this typically includes job postings in specific formats over a mandatory 30-day period. DOL reviews the recruitment results before certifying the labor application, which then becomes the foundation for your I-140 immigrant visa petition with USCIS.
Can I switch ML jobs while my green card application is pending?
Portability rules under AC21 allow you to change to a same or similar ML role once your I-140 has been approved and your I-485 adjustment of status application has been pending for at least 180 days. 'Same or similar' is evaluated against the SOC code and job duties on the original petition, so moving from one machine learning engineering role to another typically qualifies, but a significant shift in responsibilities could raise questions.