E-3 Visa Applied AI Engineer Jobs
Applied AI Engineer roles qualify for E-3 visa sponsorship as specialty occupations requiring a relevant bachelor's degree or higher. Australian professionals can secure employer sponsorship without entering a lottery, with visas renewable in two-year increments. The LCA filing and consulate appointment are the two key steps between your offer letter and your U.S. start date.
See All Applied AI Engineer JobsOverview
Showing 5 of 309+ Applied AI Engineer jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 309+ 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 JobsNVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today!
Working at the Silicon Co-design Engineering Team at NVIDIA, you will be responsible for productizing NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions. The qualified candidate should be comfortable in a lab environment and should demonstrate a passion towards creation, execution and improvement of silicon validation plans.
What you’ll be doing:
- Build and deploy AI/ML + GenAI solutions (LLMs, classical ML) to accelerate silicon co-design and validation workflows.
- Develop AI assistants and agentic systems for SCG engineers using RAG, tool-calling, and fine-tuned models.
- Create scalable data + MLOps pipelines to collect/curate chip design & validation data and support training, evaluation, and production deployment.
- Partner with cross-functional silicon teams to identify high-impact automation opportunities, integrate solutions into existing flows, and drive measurable improvements in turnaround time and quality.
- Prototype and apply modern ML techniques relevant to silicon co-design and share learnings via tech talks/knowledge sharing.
What we need to see:
- M.S. or Ph.D. (or completing within 6 months) in CS/EE/CE or related field or equivalent experience.
- Programming: Strong Python; plus C/C++ and/or Tcl/Perl/Bash.
- ML Foundation: Understanding of model development and evaluation; familiarity with Transformers/LLMs and at least one of CNN/RNN/GNN concepts.
- Frameworks: Hands-on with ML framework PyTorch / TensorFlow.
- Software Engineering: Strong fundamentals in Git, code reviews, testing, CI/CD, documentation.
- Skills: Strong debugging/problem-solving, ability to handle ambiguity, and effective communication/collaboration across HW/SW teams.
- Motivation: Interest in applying AI to semiconductor co-design/validation problems and learning the domain quickly.
Ways to stand out from the crowd:
- Familiarity with statistical methods, tools for data analysis, and analyzing large datasets to draw actionable conclusions, possibly applying deep learning techniques.
- Knowledgeable in signal integrity, timing analysis, fault analysis, sampling, computer architecture, filters.
- Familiar with lab tools (oscilloscopes and logic analyzers).
- Experience in Database and Web Development is a plus!
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We welcome you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 100,000 USD - 166,750 USD for Level 1, and 116,000 USD - 189,750 USD for Level 2.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 27, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today!
Working at the Silicon Co-design Engineering Team at NVIDIA, you will be responsible for productizing NVIDIA's chips into groundbreaking consumer, professional, server, mobile, and automotive solutions. The qualified candidate should be comfortable in a lab environment and should demonstrate a passion towards creation, execution and improvement of silicon validation plans.
What you’ll be doing:
- Build and deploy AI/ML + GenAI solutions (LLMs, classical ML) to accelerate silicon co-design and validation workflows.
- Develop AI assistants and agentic systems for SCG engineers using RAG, tool-calling, and fine-tuned models.
- Create scalable data + MLOps pipelines to collect/curate chip design & validation data and support training, evaluation, and production deployment.
- Partner with cross-functional silicon teams to identify high-impact automation opportunities, integrate solutions into existing flows, and drive measurable improvements in turnaround time and quality.
- Prototype and apply modern ML techniques relevant to silicon co-design and share learnings via tech talks/knowledge sharing.
What we need to see:
- M.S. or Ph.D. (or completing within 6 months) in CS/EE/CE or related field or equivalent experience.
- Programming: Strong Python; plus C/C++ and/or Tcl/Perl/Bash.
- ML Foundation: Understanding of model development and evaluation; familiarity with Transformers/LLMs and at least one of CNN/RNN/GNN concepts.
- Frameworks: Hands-on with ML framework PyTorch / TensorFlow.
- Software Engineering: Strong fundamentals in Git, code reviews, testing, CI/CD, documentation.
- Skills: Strong debugging/problem-solving, ability to handle ambiguity, and effective communication/collaboration across HW/SW teams.
- Motivation: Interest in applying AI to semiconductor co-design/validation problems and learning the domain quickly.
Ways to stand out from the crowd:
- Familiarity with statistical methods, tools for data analysis, and analyzing large datasets to draw actionable conclusions, possibly applying deep learning techniques.
- Knowledgeable in signal integrity, timing analysis, fault analysis, sampling, computer architecture, filters.
- Familiar with lab tools (oscilloscopes and logic analyzers).
- Experience in Database and Web Development is a plus!
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We welcome you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 100,000 USD - 166,750 USD for Level 1, and 116,000 USD - 189,750 USD for Level 2.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 27, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
See all 309+ 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 JobsTips for Finding E-3 Visa Sponsorship as an Applied AI Engineer
Frame your CV for U.S. specialty occupation standards
U.S. employers assess whether your role meets DOL's specialty occupation definition. List your degree field explicitly and align your job titles to U.S. equivalents like Machine Learning Engineer or AI Research Engineer to avoid ambiguity during LCA review.
Target employers with active LCA filing histories
Search DOL's Office of Foreign Labor Certification disclosure data to identify companies that have already filed LCAs for AI or software engineering roles. Prior LCA activity signals familiarity with E-3 sponsorship, which shortens the internal approval process.
Address E-3 eligibility before your offer stage
Raise your Australian citizenship and E-3 eligibility during late-round interviews, not after the offer. Many hiring managers confuse E-3 with H-1B and assume a lottery is involved. Clarifying upfront removes a common objection before it becomes a deal-breaker.
Use Migrate Mate's E-3 filing service for end-to-end support
Once you have an offer, use Migrate Mate's E-3 filing service to handle your LCA submission with DOL and prepare your full consulate package. This avoids the documentation gaps that cause delays at Sydney, Melbourne, or Perth appointments.
Confirm your employer's E-Verify enrollment before accepting
E-Verify enrollment is not required for most E-3 sponsors, but some large federal contractors mandate it. Verify your prospective employer's compliance status with E-Verify before signing an offer to avoid onboarding complications after your visa is issued.
Prepare documentation for an AI-specific specialty occupation case
Applied AI roles can attract consular scrutiny if the job description reads as general software development. Bring your offer letter, degree transcripts, and a detailed role description that ties your AI engineering tasks to your specific academic background at your consulate appointment.
Applied AI Engineer jobs are hiring across the US. Find yours.
Find Applied AI Engineer JobsApplied AI Engineer E-3 Visa: Frequently Asked Questions
How do I find Applied AI Engineer jobs with E-3 visa sponsorship?
Migrate Mate is built specifically for Australian professionals searching for U.S. roles that include E-3 visa sponsorship. You can filter by job title and see which employers have E-3 or LCA filing history, so you're targeting companies already set up to sponsor rather than educating every recruiter from scratch.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does an Applied AI Engineer role qualify as a specialty occupation for the E-3?
Yes, provided the position requires a bachelor's degree or higher in a directly related field such as computer science, artificial intelligence, or machine learning. Roles that accept any degree discipline or treat the degree as optional may not meet DOL's specialty occupation standard. Your offer letter and job description need to reflect a specific degree requirement to support the LCA.
How does the E-3 compare to H-1B for Applied AI Engineer positions?
The E-3 has no lottery and no annual cap, so you can apply at any time of year once you have a job offer. H-1B registrations are entered into a lottery each March with approximately 85,000 slots for the entire cap-subject pool. For Australian AI engineers, the E-3 eliminates the uncertainty that makes H-1B sponsorship a multi-year gamble for both you and your employer.
Can I switch employers on an E-3 while working in the U.S. as an Applied AI Engineer?
Yes, but each employer change requires a new LCA filing and a new E-3 visa or change of status. You cannot port an E-3 the way some other visa categories allow. If you're already in the U.S., your new employer must have a certified LCA before you start work, and you'll need to either apply at a consulate or file for a change of status with USCIS.
See which Applied AI Engineer employers are hiring and sponsoring visas right now.
Search Applied AI Engineer Jobs