Green Card Machine Learning Engineer Jobs
Machine Learning Engineer roles qualify for green card sponsorship under EB-2 for advanced-degree professionals and EB-3 for skilled workers with a bachelor's degree. Your employer files a PERM labor certification with DOL before petitioning USCIS, permanently sponsoring your residency rather than tying you to a temporary status.
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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 3,675+ Green Card Machine Learning Engineer Jobs
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Get Access To All JobsTips for Finding Green Card Sponsorship as a Machine Learning Engineer
Align your credentials to EB-2 requirements
A U.S. master's degree or a foreign equivalent in computer science, statistics, or a related field positions you for EB-2. Document your degree equivalency early, because PERM audits frequently scrutinize whether your qualifications match the job's minimum requirements.
Target employers with active PERM filing history
Search DOL OFLC disclosure data to confirm an employer has filed PERM certifications for ML Engineer roles recently. A company that has never run a PERM case for your job category faces a steeper learning curve, slowing your green card timeline considerably.
Use Migrate Mate to filter sponsoring employers
Search for Machine Learning Engineer roles on Migrate Mate to surface employers who have sponsored green cards for this specific job title, so you're applying to companies already equipped to run your PERM case from day one.
Verify your role meets DOL prevailing wage
Run your job title and work location through OFLC Wage Search before negotiating an offer. Your offered salary must meet the DOL prevailing wage for the role, or your PERM application will fail regardless of your qualifications or the employer's intent.
Clarify sponsorship scope during the offer stage
Confirm in writing whether the employer will cover premium processing for the I-140 and whether they sponsor dependents. ML Engineer roles attract competitive offers, but sponsorship terms vary widely and are rarely spelled out unless you ask directly before signing.
Check your O*NET job zone before the employer files
Machine Learning Engineer maps to O*NET job zone four or five, which supports the specialty occupation requirement underpinning both EB-2 and EB-3 eligibility. Share this with your employer's attorney to head off any PERM audit questions about whether the role requires a degree.
Green Card Machine Learning Engineer: Frequently Asked Questions
Does a Machine Learning Engineer role qualify for EB-2 or EB-3 sponsorship?
Both categories apply depending on your credentials and the employer's job description. EB-2 requires a master's degree or higher, or a bachelor's plus five years of progressive experience. EB-3 covers professionals with a bachelor's degree in a relevant field. Most ML Engineer positions specify a degree in computer science, mathematics, or statistics, which satisfies the minimum requirements for either category under PERM.
How does green card sponsorship differ from H-1B sponsorship for ML Engineers?
H-1B visa ties you to a specific employer on a temporary, renewable status and subjects you to the annual lottery. Green card sponsorship through PERM leads to permanent residency with no cap concerns at the EB-3 level for many countries and no renewal cycle. The tradeoff is time: PERM, I-140, and adjustment of status together can take two to four years for most nationalities, compared to a few months for an H-1B approval.
How do I find Machine Learning Engineer jobs where the employer will sponsor a green card?
Migrate Mate lets you filter ML Engineer roles by employers who have a documented history of PERM and I-140 sponsorship for this specific job title. That's more reliable than asking during a cold application, since many companies sponsor for some roles but not others depending on the team, budget, and headcount.
What does the PERM labor certification process look like for an ML Engineer role?
Your employer must conduct a supervised recruitment process to prove no qualified U.S. workers are available for the role at the offered wage. DOL reviews the documentation and, if certified, issues a PERM approval that the employer then uses to file an I-140 immigrant petition with USCIS on your behalf. The full PERM stage alone currently averages several months to over a year depending on whether an audit is triggered.
Can I change jobs while my green card is pending as an ML Engineer?
Once your I-140 is approved and your priority date is current, portability rules under AC21 allow you to change to a same or similar role without restarting the process. Machine Learning Engineer and related ML-focused titles are generally considered similar enough to support portability, but you'll want your new employer and immigration counsel to confirm the SOC code alignment before you switch.