Applied AI Engineer Jobs at Apple with Visa Sponsorship
Applied AI Engineer jobs at Apple sit at the intersection of machine learning research and product-scale deployment, spanning frameworks like Core ML, on-device inference, and Apple Silicon optimization. Apple sponsors a broad range of work visas for this function, making it a realistic target for international engineers with the right technical background.
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Get Access To All JobsINTRODUCTION
Apple’s Platform Architecture group develops the next generation of Apple hardware, and the tools to make it possible. Our team builds high-performance verification systems that accelerate the development of Apple silicon. We aim to push the boundaries of pre-silicon validation with simulation solutions that apply and extend principles from hardware emulation.
We are seeking an engineer to develop and deploy agentic AI workflows that automate and optimize pre-silicon validation processes. In this role, you will bridge the gap between applied artificial intelligence and Electronic Design Automation (EDA), building autonomous agents that triage errors, tune simulation parameters, and drastically reduce maintenance burdens for silicon verification teams.
DESCRIPTION
In this role, you will focus on AI based automations, infrastructure development, and continuous experimentation at the intersection of hardware design and verification.
Responsibilities
- Design and deploy autonomous AI agents to review design changes, resolve conflicts, and triage elaboration and simulation errors.
- Develop AI-driven workflows to flag simulation performance and design concerns, automatically tune design parameters, and explore optimization candidates autonomously.
- Apply internal and external EDA tools (e.g., Logic Equivalence Checking, wave dumps, design libraries) to automatically diagnose issues and explore design alternatives.
- Build and maintain AI harnesses, scripts, and infrastructure to support continuous research and experimentation.
- Conduct data-driven experimentation to optimize prompts and harnesses; measure and improve token efficiency, task completion, and hallucination rates.
- Track and evaluate emerging machine learning and Large Language Model (LLM) use cases in the broader industry for application in silicon design workflows.
- Occasionally travel (approximately once a year) to collaborate with development groups in the US.
MINIMUM QUALIFICATIONS
- Bachelor’s degree in Computer Science, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience).
- Experience in one of the following two areas: Applied AI (experience building, deploying, and maintaining LLM-based applications, agentic workflows, or advanced prompt engineering, combined with an entry-level familiarity with EDA tools or hardware verification concepts), or EDA/Silicon (experience with RTL design, simulation, or hardware emulation platforms, combined with a demonstrated track record of working in research-oriented roles applying software automation or ML to hardware problems).
- Experience with scripting, infrastructure development, and software engineering (e.g., Python, C/C++).
PREFERRED QUALIFICATIONS
- Master’s in Computer Science, Electrical Engineering, or a related AI/Hardware field.
- Hands-on experience with Design Verification tasks requiring application of EDA tools, including Logic Equivalence Checking (LEC), linting / static analysis tools, waveform debugging, and simulation / emulation flows.
- Familiarity with Verilog, SystemVerilog, or architecting HDL testbenches for functional verification.
- Experience developing software tools for co-simulating designs across multiple high-performance platforms.
- Comfortable exploring unfamiliar codebases, researching cutting-edge techniques, and rapidly prototyping automated solutions.
- Experience applying research methods: literature review, data-driven experimentation, analyzing results.
- Strong communication skills, with the ability to collaborate effectively with cross-functional silicon engineering, design verification, and EDA development teams.
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 $126,800 and $220,900, 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.
INTRODUCTION
Apple’s Platform Architecture group develops the next generation of Apple hardware, and the tools to make it possible. Our team builds high-performance verification systems that accelerate the development of Apple silicon. We aim to push the boundaries of pre-silicon validation with simulation solutions that apply and extend principles from hardware emulation.
We are seeking an engineer to develop and deploy agentic AI workflows that automate and optimize pre-silicon validation processes. In this role, you will bridge the gap between applied artificial intelligence and Electronic Design Automation (EDA), building autonomous agents that triage errors, tune simulation parameters, and drastically reduce maintenance burdens for silicon verification teams.
DESCRIPTION
In this role, you will focus on AI based automations, infrastructure development, and continuous experimentation at the intersection of hardware design and verification.
Responsibilities
- Design and deploy autonomous AI agents to review design changes, resolve conflicts, and triage elaboration and simulation errors.
- Develop AI-driven workflows to flag simulation performance and design concerns, automatically tune design parameters, and explore optimization candidates autonomously.
- Apply internal and external EDA tools (e.g., Logic Equivalence Checking, wave dumps, design libraries) to automatically diagnose issues and explore design alternatives.
- Build and maintain AI harnesses, scripts, and infrastructure to support continuous research and experimentation.
- Conduct data-driven experimentation to optimize prompts and harnesses; measure and improve token efficiency, task completion, and hallucination rates.
- Track and evaluate emerging machine learning and Large Language Model (LLM) use cases in the broader industry for application in silicon design workflows.
- Occasionally travel (approximately once a year) to collaborate with development groups in the US.
MINIMUM QUALIFICATIONS
- Bachelor’s degree in Computer Science, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience).
- Experience in one of the following two areas: Applied AI (experience building, deploying, and maintaining LLM-based applications, agentic workflows, or advanced prompt engineering, combined with an entry-level familiarity with EDA tools or hardware verification concepts), or EDA/Silicon (experience with RTL design, simulation, or hardware emulation platforms, combined with a demonstrated track record of working in research-oriented roles applying software automation or ML to hardware problems).
- Experience with scripting, infrastructure development, and software engineering (e.g., Python, C/C++).
PREFERRED QUALIFICATIONS
- Master’s in Computer Science, Electrical Engineering, or a related AI/Hardware field.
- Hands-on experience with Design Verification tasks requiring application of EDA tools, including Logic Equivalence Checking (LEC), linting / static analysis tools, waveform debugging, and simulation / emulation flows.
- Familiarity with Verilog, SystemVerilog, or architecting HDL testbenches for functional verification.
- Experience developing software tools for co-simulating designs across multiple high-performance platforms.
- Comfortable exploring unfamiliar codebases, researching cutting-edge techniques, and rapidly prototyping automated solutions.
- Experience applying research methods: literature review, data-driven experimentation, analyzing results.
- Strong communication skills, with the ability to collaborate effectively with cross-functional silicon engineering, design verification, and EDA development teams.
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 $126,800 and $220,900, 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 60+ Applied AI Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Applied AI Engineer Jobs at Apple.
Get Access To All JobsTips for Finding Applied AI Engineer Jobs at Apple
Align your portfolio to Apple's on-device AI stack
Apple's Applied AI roles prioritize experience with on-device inference, model compression, and privacy-preserving ML. Before applying, restructure your portfolio to surface projects using Core ML, Metal Performance Shaders, or similar edge deployment frameworks that reflect Apple's product constraints.
Target roles across multiple Apple orgs
Applied AI Engineer openings at Apple appear across Siri, Photos, Health, and the Platform Architecture group. Each org has different hiring velocity, so tracking postings across all of them increases your chances of landing in an active headcount cycle rather than a frozen one.
Clarify your visa type before the offer stage
Apple sponsors several nonimmigrant categories, and which one applies to you affects timeline and cost. Australians on E-3 and Canadians on TN move faster through the process than H-1B cap-subject applicants, so surface your citizenship early so the recruiting team routes you correctly.
Understand the H-1B cap and its timing constraints
If you need a cap-subject H-1B, USCIS only accepts registrations in March for an October 1 start. If you miss the lottery window or aren't selected, you'll need to negotiate a delayed start or explore whether Apple can convert an existing status like F-1 OPT as a bridge.
Verify your OPT STEM extension eligibility early
Apple is E-Verify enrolled, which is a requirement for the 24-month STEM OPT extension. If you're on F-1 OPT with a degree in computer science, electrical engineering, or a related CIP-coded field, confirm your eligibility with your DSO before accepting an offer to avoid gaps in work authorization.
Use Migrate Mate to filter Apple AI roles by visa type
Applied AI Engineer jobs at Apple don't always surface easily when filtered by sponsorship on general job boards. Migrate Mate lets you search specifically for Apple roles that match your visa category, so you're not wasting applications on postings that won't support your situation.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Applied AI Engineers?
Yes, Apple sponsors H-1B visas for Applied AI Engineer roles. If you're subject to the annual H-1B cap, your employer registration must be submitted in March for a lottery draw, with employment starting no earlier than October 1. Apple also sponsors H-1B1 visas for Chilean and Singaporean nationals, which bypass the lottery entirely.
How do I apply for Applied AI Engineer jobs at Apple?
Apply through Apple's careers portal at jobs.apple.com or browse filtered listings on Migrate Mate, which surfaces roles by visa sponsorship type. Applied AI Engineer positions at Apple typically require a technical screen, followed by multiple rounds covering ML system design, coding, and a domain-specific deep dive relevant to the team you're interviewing with.
Which visa types does Apple commonly use for Applied AI Engineers?
Apple sponsors H-1B, H-1B1 visa, E-3 visa, TN visa, F-1 OPT, and F-1 CPT for Applied AI Engineer roles, as well as employment-based Green Card categories including EB-2 and EB-3. The right category depends on your nationality and current status. Australians typically use the E-3 visa, Canadians the TN visa, and most others the H-1B, subject to the annual lottery.
What qualifications does Apple expect for Applied AI Engineer roles?
Apple's Applied AI Engineer roles generally require a master's or PhD in machine learning, computer science, or electrical engineering, combined with hands-on experience deploying models at scale. Familiarity with Apple's specific constraints, including on-device inference, low-latency pipelines, and privacy-first architectures, carries significant weight alongside general deep learning expertise.
How long does the visa sponsorship process take for an Apple Applied AI Engineer offer?
Timeline depends heavily on visa type. E-3 and TN approvals can happen within weeks of an offer. H-1B transfers for existing H-1B holders can begin on the date USCIS receives the petition. Cap-subject H-1B candidates face a longer path, with employment starting no earlier than October 1 following a March lottery registration. USCIS premium processing can reduce adjudication to 15 business days once the petition is filed.