Green Card Applied AI Engineer Jobs
Applied AI Engineer roles qualify for green card sponsorship under EB-2 for advanced-degree professionals or EB-3 for skilled workers, with employers filing PERM labor certification through DOL before submitting an I-140 petition to USCIS. Priority dates and country backlogs vary, so starting the sponsorship process early matters.
Find Green Card Applied AI Engineer JobsOverview
Showing 5 of 459+ Applied AI Engineer jobs
See all 459+ Applied AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Applied AI Engineer roles.
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 459+ Green Card Applied AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Green Card Applied AI Engineer Jobs.
Get Access To All JobsTips for Finding Green Card Sponsorship as an Applied AI Engineer
Document your AI specialization precisely
PERM requires your job duties to match your credentials exactly. List specific frameworks, model architectures, and deployment environments you've worked with so your employer can build a labor certification that reflects your actual role, not a generic software engineer description.
Target employers with PERM filing history
Search OFLC Wage Search to verify that a prospective employer has filed PERM applications for AI or machine learning roles before. Employers new to PERM sponsorship often underestimate the timeline, which can stall your case after you've already joined.
Find green card sponsors on Migrate Mate
Use Migrate Mate to filter Applied AI Engineer roles by employers who actively sponsor EB-2 and EB-3 green cards. Seeing verified sponsorship history upfront saves you from raising the subject with employers who have no PERM infrastructure in place.
Clarify EB-2 versus EB-3 with your employer early
Applied AI Engineer positions can qualify under either category depending on how the employer defines minimum requirements. EB-2 requires a master's degree or equivalent, while EB-3 covers roles requiring a bachelor's. The category affects your priority date and, for some nationalities, your wait time significantly.
Request the PERM start date before accepting an offer
Ask specifically when your employer plans to begin the prevailing wage determination with DOL. PERM requires a formal PWD before recruitment can start, and that process alone can take several months, pushing your I-140 filing further than most candidates expect.
Check your O*NET occupation profile against your job duties
USCIS scrutinizes whether Applied AI Engineer duties constitute a specialty occupation. Reviewing the O*NET profile for your SOC code helps you confirm that your role aligns with published degree requirements, which strengthens both the PERM application and any subsequent RFE response.
Green Card Applied AI Engineer: Frequently Asked Questions
Do Applied AI Engineer roles qualify for EB-2 or EB-3 green card sponsorship?
Most Applied AI Engineer positions qualify under EB-2 if the employer requires a master's degree or you can demonstrate the equivalent through a combination of a bachelor's degree and five or more years of progressive experience. EB-3 applies when the role requires a bachelor's degree as the minimum. The classification affects your priority date and, for nationals of high-backlog countries like India and China, can meaningfully change your wait time.
How does the green card process differ from H-1B sponsorship for this role?
H-1B visa sponsorship grants temporary status in two-year or three-year increments and is subject to annual lottery caps. The EB-2 and EB-3 green card process leads to permanent residency and has no annual employer cap for most nationalities, though per-country limits create backlogs for applicants from India and China. The PERM labor certification process also requires your employer to conduct a formal recruitment campaign before filing, which adds three to twelve months before USCIS even receives the I-140 petition.
How long does the PERM process typically take for an Applied AI Engineer?
The DOL prevailing wage determination currently runs several months, followed by the supervised recruitment period of at least 30 days, then PERM audit risk adds further variance. From the day your employer begins the PWD request to an approved I-140 at USCIS, plan for 18 to 30 months in a standard case without an audit. Premium processing is available for I-140 but not for PERM, so the DOL phase cannot be accelerated.
What should I look for in an employer willing to sponsor a green card?
Look for employers who have filed PERM applications for AI or machine learning roles in the past two years, have dedicated immigration counsel rather than ad hoc vendor relationships, and are willing to state a clear PERM start date in your offer letter. You can search for Applied AI Engineer roles at employers with verified green card sponsorship history on Migrate Mate, which filters by sponsorship type so you're only seeing companies that have already committed to the process.
Can I change jobs after my employer files my PERM application?
Changing employers resets the PERM process entirely because the application is tied to a specific employer and a specific job description. If your I-140 has been approved and has been pending for 180 days or more, portability rules under AC21 allow you to move to a similar role at a new employer without losing your priority date. For most Applied AI Engineer candidates early in the process, leaving before I-140 approval means starting over with a new sponsor.