H-1B1 Singapore Visa Applied AI Engineer Jobs
Applied AI Engineer roles qualify for H-1B1 Singapore visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, AI, or a related field. Singapore nationals bypass the H-1B lottery entirely, with the 5,400-visa annual cap rarely approached and consulate processing typically faster than USCIS petition review.
Find H-1B1 Singapore Visa Applied AI Engineer JobsOverview
Showing 5 of 73+ Applied AI Engineer jobs
See all 73+ 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 73+ H-1B1 Singapore Visa Applied AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa Applied AI Engineer Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as an Applied AI Engineer
Translate your credentials into U.S. equivalency
Singapore's four-year NUS or NTU computer science degrees satisfy the H-1B1 visa specialty occupation degree requirement directly. If your program was three years, document coursework and credit hours upfront so the employer's attorney can confirm equivalency before filing.
Target employers with active LCA filing history
Use Migrate Mate to filter Applied AI Engineer roles by employers who have previously filed Labor Condition Applications for this occupation code, cutting out companies unfamiliar with H-1B1 Singapore sponsorship before you invest time in interviews.
Distinguish H-1B1 status when briefing hiring managers
Many U.S. recruiters conflate H-1B1 with H-1B and assume a lottery is involved. Clarify upfront that H-1B1 Singapore requires no lottery, no USCIS petition, and is consulate-processed, which removes the April registration deadline constraint entirely.
Verify the employer's prevailing wage tier for your role
Applied AI Engineer roles frequently fall at DOL wage Level III or IV. Run the OFLC Wage Search using the correct SOC code before your offer stage so you can flag misclassified wage tiers before the Labor Condition Application is filed.
Confirm your job duties satisfy specialty occupation criteria
Pull the O*NET profile for Applied AI Engineer to see the listed knowledge domains and typical degree requirements. Cross-reference your actual day-to-day duties against that profile before your visa interview, since consular officers assess specialty occupation independently of the employer's LCA.
Negotiate filing timeline into your start-date agreement
H-1B1 visa consulate processing in Singapore can run two to four weeks after your DS-160 and interview. Build that buffer into your offer letter's start date so your employer's payroll and onboarding timelines aren't disrupted by realistic processing gaps.
Frequently Asked Questions
Does an Applied AI Engineer role qualify as a specialty occupation for the H-1B1 Singapore visa?
Yes. Applied AI Engineer positions require at least a bachelor's degree in computer science, machine learning, or a closely related field, which satisfies the H-1B1 visa specialty occupation definition. USCIS and consular officers assess whether the specific duties require that theoretical and practical application of highly specialized knowledge, so your job description should reflect those technical requirements explicitly.
How does the H-1B1 Singapore visa differ from H-1B for an Applied AI Engineer?
The H-1B1 Singapore visa has no lottery, no USCIS petition requirement, and a separate 5,400-visa annual cap that has never been exhausted. You apply directly at the U.S. Embassy in Singapore after your employer files a certified Labor Condition Application with DOL. H-1B requires USCIS registration in April, a lottery selection, and a petition approval before any consular step, adding months to the process.
How do I find U.S. employers willing to sponsor an H-1B1 Singapore visa for AI engineering roles?
Migrate Mate surfaces Applied AI Engineer jobs filtered by employers who have active H-1B1 visa and LCA filing history, so you're not cold-applying to companies unfamiliar with Singapore visa sponsorship. Focusing your search on employers with a documented track record of sponsoring this visa type substantially reduces the risk of an offer falling through at the filing stage.
Can I switch employers after arriving in the U.S. on an H-1B1 Singapore visa?
Yes, but each new employer must file a new Labor Condition Application and you must obtain a new H-1B1 visa stamp at a consulate before starting with them. Unlike H-1B, there is no portability provision allowing you to begin work immediately upon a transfer petition being filed, so plan for consulate processing time between roles.
What documents should a Singaporean Applied AI Engineer prepare before the visa interview?
Bring your certified LCA, a support letter from your U.S. employer detailing your AI engineering duties and required qualifications, your academic transcripts and degree certificates, your DS-160 confirmation, and evidence of your nonimmigrant intent. If your Singapore degree was three years rather than four, include a course-by-course credential evaluation addressing U.S. equivalency, since consular officers may raise the issue independently of the LCA.