H-1B Visa Applied AI Engineer Jobs
Applied AI Engineer roles sit squarely within H-1B visa specialty occupation requirements, with employers filing Labor Condition Applications under SOC codes tied to software development and machine learning engineering. The cap-subject lottery applies unless your employer holds cap-exempt status, so timing your job search around the April registration window matters.
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Get Access To All JobsThe Health Personalization team builds AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing. We harness large language models and the latest ML advances to build products that are useful, personal, privacy-preserving, and safe - turning research and incubation into features people rely on every day. As part of the larger Sensor Software & Prototyping team, we work across hardware platforms and data modalities including wearables and natural language input. We are committed to building deeply personal features that understand, anticipate, and adapt to users' behaviors and uphold Apple's deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us!
Description
In this role, you will prototype, develop, evaluate, and ship Generative AI experiences for real-world health and wellbeing applications. You'll apply strong ML fundamentals, build practical evaluation methods, and ground your work in real on-device user interactions. Your work will directly shape customer-facing health products across the full ML lifecycle.
A strong candidate makes progress through ambiguity - building, learning from real data, and iterating toward the right answer rather than waiting for the perfect plan. They take ownership of outcomes end-to-end, prioritize well, and learn fast.
Responsibilities
-
Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle - prototyping on-device experiences to explore design directions, and shipping production-quality features.
-
Independently design, run, and analyze ML experiments to deliver measurable quality improvements.
-
Design and implement evaluation frameworks - including automated assessment tools, LLM-based autograders, and benchmarks - to measure and improve model quality.
-
Analyze algorithm and feature behavior, identify failure modes, and drive actionable improvements through experimentation and failure analysis - verifying that fixes hold with data.
-
Work cross-functionally with many teams - including clinical experts, designers, and HW and SW teams, and more - to bring features into production with real-world applicability and impact.
Minimum Qualifications
BS and a minimum of 3 years relevant industry experience
Ability to leverage AI-assisted tooling to write clean, performant code (e.g. Python), while maintaining full ownership of code quality and software development best practices (e.g. Git).
Technical expertise and hands-on experience building and evaluating machine learning solutions for user-facing applications.
Comfort building functional prototypes or proof-of-concept demos to test ideas quickly.
Preferred Qualifications
MS or PhD in computer science, machine learning, health informatics, biomedical engineering, or a related quantitative field - or equivalent industry experience.
Strong communication skills and ability to work cross-functionally with technical and non-technical stakeholders.
Technical expertise in generative AI domains, such as large language model architectures, knowledge retrieval, and natural language understanding.
Deep expertise with LLM-based evaluation systems and evidence-based approaches to test development and quality measurement.
Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products.
Experience building and deploying performant on-device or full-stack systems, including rapid prototyping of user-facing experiences (e.g. Swift, SwiftUI), is a plus.
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 $150,400 and $277,600, 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
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
The Health Personalization team builds AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing. We harness large language models and the latest ML advances to build products that are useful, personal, privacy-preserving, and safe - turning research and incubation into features people rely on every day. As part of the larger Sensor Software & Prototyping team, we work across hardware platforms and data modalities including wearables and natural language input. We are committed to building deeply personal features that understand, anticipate, and adapt to users' behaviors and uphold Apple's deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us!
Description
In this role, you will prototype, develop, evaluate, and ship Generative AI experiences for real-world health and wellbeing applications. You'll apply strong ML fundamentals, build practical evaluation methods, and ground your work in real on-device user interactions. Your work will directly shape customer-facing health products across the full ML lifecycle.
A strong candidate makes progress through ambiguity - building, learning from real data, and iterating toward the right answer rather than waiting for the perfect plan. They take ownership of outcomes end-to-end, prioritize well, and learn fast.
Responsibilities
-
Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle - prototyping on-device experiences to explore design directions, and shipping production-quality features.
-
Independently design, run, and analyze ML experiments to deliver measurable quality improvements.
-
Design and implement evaluation frameworks - including automated assessment tools, LLM-based autograders, and benchmarks - to measure and improve model quality.
-
Analyze algorithm and feature behavior, identify failure modes, and drive actionable improvements through experimentation and failure analysis - verifying that fixes hold with data.
-
Work cross-functionally with many teams - including clinical experts, designers, and HW and SW teams, and more - to bring features into production with real-world applicability and impact.
Minimum Qualifications
BS and a minimum of 3 years relevant industry experience
Ability to leverage AI-assisted tooling to write clean, performant code (e.g. Python), while maintaining full ownership of code quality and software development best practices (e.g. Git).
Technical expertise and hands-on experience building and evaluating machine learning solutions for user-facing applications.
Comfort building functional prototypes or proof-of-concept demos to test ideas quickly.
Preferred Qualifications
MS or PhD in computer science, machine learning, health informatics, biomedical engineering, or a related quantitative field - or equivalent industry experience.
Strong communication skills and ability to work cross-functionally with technical and non-technical stakeholders.
Technical expertise in generative AI domains, such as large language model architectures, knowledge retrieval, and natural language understanding.
Deep expertise with LLM-based evaluation systems and evidence-based approaches to test development and quality measurement.
Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products.
Experience building and deploying performant on-device or full-stack systems, including rapid prototyping of user-facing experiences (e.g. Swift, SwiftUI), is a plus.
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 $150,400 and $277,600, 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
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See all 806+ H-1B Visa Applied AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Applied AI Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an Applied AI Engineer
Map your degree to AI engineering SOC codes
USCIS evaluates whether your specific degree field directly relates to the Applied AI Engineer role. Pull the O*NET profile for your target SOC code and confirm your transcript language aligns before your employer files the I-129.
Use Migrate Mate to filter verified sponsors
Search Applied AI Engineer roles on Migrate Mate to surface employers with active LCA filing history for AI and ML positions, so you're targeting companies that have already cleared DOL prevailing-wage certification for this role type.
Check prevailing wage before negotiating your offer
Run your target job title, location, and Level I through IV wage tier through the OFLC Wage Search before your offer call. Your employer must pay at or above the prevailing wage on the certified LCA or your H-1B petition is defective from day one.
Verify your employer's E-Verify enrollment early
AI roles at early-stage startups frequently lack E-Verify enrollment, which blocks STEM OPT extensions and complicates future H-1B transfers. Confirm enrollment status during the interview stage, not after you've signed an offer letter.
Request premium processing if your OPT cap-gap is tight
If your OPT expires before October 1 and your employer filed after April 1, your authorized stay depends on an approved H-1B before status lapses. Premium processing cuts USCIS adjudication to 15 business days and removes that gap risk.
Document your AI project scope for specialty occupation evidence
Applied AI Engineer petitions increasingly face RFEs questioning whether the role truly requires a bachelor's degree in a specific field. Prepare job-duty narratives that name specific ML frameworks, model architectures, and research methodologies tied directly to your degree discipline.
H-1B Visa Applied AI Engineer: Frequently Asked Questions
Does an Applied AI Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, provided the position requires a bachelor's degree or higher in a directly related field such as computer science, machine learning, mathematics, or a closely aligned engineering discipline. Employers strengthen the case by tying specific job duties, like fine-tuning large language models or designing inference pipelines, to degree-level theoretical knowledge. Generic software engineering duties without AI-specific requirements can weaken the specialty occupation argument at adjudication.
Which SOC codes do employers typically use when filing H-1B LCAs for Applied AI Engineer positions?
Most employers file under SOC 15-2051 (Data Scientists), 15-1252 (Software Developers, Quality Assurance Analysts, and Testers), or 15-1299 (Computer and Information Technology Occupations, All Other). The SOC code determines which prevailing wage level USCIS and DOL apply to the petition, so confirming the code your employer intends to use before the LCA is certified protects your offer terms.
How do I find Applied AI Engineer employers that actively sponsor H-1B visas?
Search on Migrate Mate, which surfaces employers with verified LCA filing history for AI and machine learning roles. This lets you focus your applications on companies that have already navigated DOL prevailing-wage certification for this role type rather than spending time on employers who have no H-1B sponsorship track record.
Can an Applied AI Engineer role at a startup or small company support an H-1B petition?
Yes, employer size doesn't determine H-1B eligibility, but smaller AI companies introduce specific risks. Startups may lack E-Verify enrollment, may struggle to document that the role genuinely requires a specialty-degree holder, or may not have the financial stability USCIS expects when assessing ability to pay. Asking for audited financials or a signed offer with defined salary terms before the petition is filed is reasonable due diligence.
What happens to my H-1B if my employer pivots away from AI projects after I'm sponsored?
Your H-1B is tied to the job duties and SOC code certified on the original LCA. If your duties shift materially away from the AI engineering work described in the petition, your employer should amend the H-1B with USCIS before the change takes effect. Working in a materially different role without an amended petition creates status compliance risk, and USCIS can issue an RFE or denial on extension if duties no longer match.