TN Visa Machine Learning Jobs
Machine Learning roles qualify for TN visa sponsorship under the Engineer or Computer Systems Analyst categories, depending on how the position is structured. Canadian citizens can secure TN status at the border with no cap or lottery. Mexican citizens require a consular appointment. A qualifying bachelor's degree in a technical field is required.
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Get Access To All JobsINTRODUCTION
The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers, and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a senior engineer excited about solving real-world problems in the health domain that make a difference in our customers' lives.
DESCRIPTION
In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning models and systems. You will solve ambitious problems involving unique data and high-impact products, including state-of-the-art generative AI technologies. The successful candidate should possess excellent interpersonal skills and the ability to work cross-functionally to rapidly apply engineering best practices and novel research techniques at the intersection of Health, ML, and consumer products.
MINIMUM QUALIFICATIONS
- 10+ years of overall software development experience.
- Experience leading a team and/or a proven track record of cross-functional collaboration to deliver customer-facing features with machine learning capabilities in production.
- BS/MS/Ph.D. in Computer Science, Computer Engineering, Machine Learning, or related fields (or equivalent qualification).
PREFERRED QUALIFICATIONS
- Ph.D. in Computer Science, Machine Learning, or a related field.
- Strong background in generative models, natural language processing (NLP), and large language models (LLMs).
- 5+ years of hands-on experience in state-of-the-art machine learning and deep learning applied to large-scale datasets and/or production applications.
- Proficiency developing and working with large-scale models using modern machine learning packages (e.g., TensorFlow, PyTorch, Jax, Huggingface).
- Proficiency in building and troubleshooting modern agentic systems (prompt tuning, routing, planning, multi-agent, RAG, tool use, memory management, etc.).
- Experience with healthcare data, products, and workflows.
- Ability to thrive in a fast-paced environment, deal with uncertainty, and adapt to new and changing requirements.
- Proven track record of contributing to diverse teams in a collaborative environment.
- A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $212,000 and $386,300, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
INTRODUCTION
The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers, and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a senior engineer excited about solving real-world problems in the health domain that make a difference in our customers' lives.
DESCRIPTION
In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning models and systems. You will solve ambitious problems involving unique data and high-impact products, including state-of-the-art generative AI technologies. The successful candidate should possess excellent interpersonal skills and the ability to work cross-functionally to rapidly apply engineering best practices and novel research techniques at the intersection of Health, ML, and consumer products.
MINIMUM QUALIFICATIONS
- 10+ years of overall software development experience.
- Experience leading a team and/or a proven track record of cross-functional collaboration to deliver customer-facing features with machine learning capabilities in production.
- BS/MS/Ph.D. in Computer Science, Computer Engineering, Machine Learning, or related fields (or equivalent qualification).
PREFERRED QUALIFICATIONS
- Ph.D. in Computer Science, Machine Learning, or a related field.
- Strong background in generative models, natural language processing (NLP), and large language models (LLMs).
- 5+ years of hands-on experience in state-of-the-art machine learning and deep learning applied to large-scale datasets and/or production applications.
- Proficiency developing and working with large-scale models using modern machine learning packages (e.g., TensorFlow, PyTorch, Jax, Huggingface).
- Proficiency in building and troubleshooting modern agentic systems (prompt tuning, routing, planning, multi-agent, RAG, tool use, memory management, etc.).
- Experience with healthcare data, products, and workflows.
- Ability to thrive in a fast-paced environment, deal with uncertainty, and adapt to new and changing requirements.
- Proven track record of contributing to diverse teams in a collaborative environment.
- A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $212,000 and $386,300, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
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Get Access To All JobsTips for Finding TN Visa Sponsorship as a Machine Learning
Match your degree to the TN category
TN approval for Machine Learning roles depends on whether your employer files under Engineer or Computer Systems Analyst. Your degree field must align with whichever category the job description supports. A mismatch is the most common denial trigger.
Target employers with active ML research teams
Companies running dedicated Machine Learning infrastructure are more likely to understand work visa sponsorship processes. Look for job postings from employers with recent visa filings, research publications, or roles requiring specialized technical degrees, which signal prior experience navigating work authorization requirements.
Prepare your credential documents before applying
Gather your degree transcripts, any credential evaluations, and a detailed job description before you start applications. Canadian citizens presenting at the port of entry need everything ready on the spot since CBSA reviews documentation immediately.
Use Migrate Mate to filter for TN-ready employers
Searching broadly wastes time on employers unfamiliar with TN visa mechanics. Migrate Mate lets you filter Machine Learning roles by companies that have sponsored TN or similar work visas, so you focus on employers who won't need education on the process.
Clarify the job title before the offer stage
Job titles in Machine Learning vary widely. 'AI Engineer,' 'Data Scientist,' and 'ML Researcher' can map to different TN categories. Confirm with your prospective employer which title will appear on the support letter before any filing or border appointment.
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Find Machine Learning JobsMachine Learning TN Visa: Frequently Asked Questions
Does a Machine Learning job qualify for a TN visa?
Machine Learning roles can qualify under the Engineer or Computer Systems Analyst TN category, depending on how the job duties are framed and your degree field. The role must require at least a bachelor's degree in a directly related technical discipline. A generic 'technology' degree without clear alignment to the job description can cause problems at the border or consulate.
How does TN compare to H-1B for Machine Learning professionals?
TN is often faster and more predictable for Machine Learning roles than H-1B. Canadians can get TN status at the port of entry in a single day, with no lottery and no cap. H-1B requires an annual lottery with roughly a 25 percent selection rate and a six-month wait. Mexican nationals face a TN cap of 5,500 per year, so H-1B may be worth pursuing as a parallel path if you anticipate long-term U.S. employment.
Can a Canadian Machine Learning professional get TN status without a job offer already in hand?
No. TN status requires a concrete job offer from a specific U.S. employer before you can apply. You cannot get TN status speculatively or as a job-search visa. The offer letter must describe your duties, confirm the TN category, and state the employment period. Only after that letter exists can a Canadian present at the border or a Mexican schedule a consular appointment.
Where can I find Machine Learning jobs where the employer is already familiar with TN sponsorship?
Migrate Mate is built specifically for this search. It surfaces Machine Learning roles at companies with documented work visa sponsorship history, so you avoid spending time on employers who will decline or delay because they don't understand TN mechanics. Searching with that filter significantly shortens the time between application and offer.
What happens if my TN visa is denied at the border for a Machine Learning role?
If CBSA or CBP denies your TN application, you can reapply at a different port of entry or consulate once you've addressed the reason for denial, which is typically a documentation gap or a degree-to-job mismatch. There is no mandatory waiting period for reapplication. You should revise your support letter and, if the category was the issue, confirm with your employer that the job description supports the intended TN classification before reapplying.
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