E-3 Visa AI Specialist Jobs
AI Specialist roles in machine learning, NLP, and computer vision qualify as E-3 specialty occupations, making U.S. employer sponsorship straightforward for Australian nationals with a relevant degree. The E-3 has no lottery and no annual cap, so you can target roles and start the process year-round without waiting for a selection cycle.
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AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and committed support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow.
Are you passionate about Artificial Intelligence, Machine Learning, and GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art genAI/ML tools on Amazon Web Service (AWS)? Come join us!
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning, as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition with deep learning; as is Prime Air. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.
AWS is looking for a genAI/ML Solutions Architect who will be the Subject Matter Expert for helping customers in the United States design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage genAI on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.
You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building machine learning models. You will be familiar with the ecosystem of software vendors in the genAI space, and will leverage this knowledge to help AWS customers in their selection process.
Travel up to 50% across the United States may be possible.
Key job responsibilities
-
Working with customers’ development and data science teams to deeply understand their business and technical needs. After understanding their needs, you will design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services including SageMaker, Amazon Bedrock, Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Personalize, and the other AI/ML services.
-
Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment in the AMERICAS for Amazon SageMaker and related services that support GenAI use cases.
-
Thought Leadership – Evangelize AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
-
Act as a technical liaison between customers and the AWS SageMaker or other service teams to provide customer driven product improvement feedback.
-
Develop and support an AWS internal community of GenAI related subject matter experts in the AMERICAS.
A day in the life
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
BASIC QUALIFICATIONS
-
4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
-
2+ years of design, implementation, or consulting in applications and infrastructures experience
PREFERRED QUALIFICATIONS
-
Experience working within software development or Internet-related industries
-
Experience migrating or transforming legacy customer solutions to the cloud
-
Experience working with AWS technologies from a dev/ops perspective
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, NY, New York - 144,500.00 - 195,400.00 USD annually
DESCRIPTION
AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and committed support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow.
Are you passionate about Artificial Intelligence, Machine Learning, and GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art genAI/ML tools on Amazon Web Service (AWS)? Come join us!
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning, as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition with deep learning; as is Prime Air. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.
AWS is looking for a genAI/ML Solutions Architect who will be the Subject Matter Expert for helping customers in the United States design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage genAI on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.
You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building machine learning models. You will be familiar with the ecosystem of software vendors in the genAI space, and will leverage this knowledge to help AWS customers in their selection process.
Travel up to 50% across the United States may be possible.
Key job responsibilities
-
Working with customers’ development and data science teams to deeply understand their business and technical needs. After understanding their needs, you will design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services including SageMaker, Amazon Bedrock, Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Personalize, and the other AI/ML services.
-
Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment in the AMERICAS for Amazon SageMaker and related services that support GenAI use cases.
-
Thought Leadership – Evangelize AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
-
Act as a technical liaison between customers and the AWS SageMaker or other service teams to provide customer driven product improvement feedback.
-
Develop and support an AWS internal community of GenAI related subject matter experts in the AMERICAS.
A day in the life
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
BASIC QUALIFICATIONS
-
4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
-
2+ years of design, implementation, or consulting in applications and infrastructures experience
PREFERRED QUALIFICATIONS
-
Experience working within software development or Internet-related industries
-
Experience migrating or transforming legacy customer solutions to the cloud
-
Experience working with AWS technologies from a dev/ops perspective
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, NY, New York - 144,500.00 - 195,400.00 USD annually
See all 81+ AI Specialist jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Specialist roles.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as an AI Specialist
Align your credentials to specialty occupation standards
USCIS requires your degree field to match the AI Specialist role directly. A computer science or data science degree maps cleanly, but an adjacent degree like mathematics or electrical engineering needs a clear connection to the specific job duties in your offer letter.
Target employers with active LCA filing history
Search the DOL's public LCA disclosure data to identify companies that have already certified AI and machine learning roles. Employers with existing LCAs for similar job titles understand the E-3 process and are far less likely to withdraw an offer over sponsorship concerns.
Use Migrate Mate's E-3 filing service for post-offer paperwork
Once you have a written offer, your employer needs to file a certified LCA with the DOL before you can apply at the consulate. Use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork so nothing delays your start date.
Secure a support letter detailing AI specialty duties
Ask your employer to write a detailed support letter explaining why the AI Specialist role requires a specialized degree, not just any bachelor's. Vague job descriptions are a common reason consular officers ask follow-up questions at Australian posts.
Book your consulate appointment as soon as the LCA is certified
DOL certifies most LCAs within seven business days. Schedule your visa interview at Sydney, Melbourne, or Perth immediately after certification. Appointment availability varies by post, and delays between certification and scheduling can push back your U.S. start date by weeks.
AI Specialist jobs are hiring across the US. Find yours.
Find AI Specialist JobsAI Specialist E-3 Visa: Frequently Asked Questions
How do I find AI Specialist jobs that offer E-3 visa sponsorship?
Search Migrate Mate to filter AI Specialist roles by E-3 sponsorship specifically. Most general job boards don't distinguish between visa types, so you end up filtering manually through roles that only consider H-1B candidates. Migrate Mate surfaces employers who have filed for E-3 or equivalent specialty occupation positions, saving you from outreach that goes nowhere.
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 AI Specialist role qualify as a specialty occupation for the E-3?
Yes, in most cases. USCIS defines a specialty occupation as one that normally requires a bachelor's degree or higher in a specific field. AI Specialist roles involving machine learning model development, NLP engineering, or computer vision research consistently meet this standard. Roles with vague titles like 'AI generalist' or duties that don't require a specific degree field can be harder to support, so your offer letter's duty description matters.
How does the E-3 compare to H-1B for AI Specialist roles in the U.S.?
The E-3 is available only to Australian nationals, but for those who qualify it has significant practical advantages over the H-1B. There's no annual lottery, no cap, and no waiting for a fiscal year registration window. You can apply for an E-3 any time of year as long as you have a qualifying offer and a certified LCA. H-1B registrations are capped at 85,000 per year and require lottery selection before any petition can even be filed.
Can I change AI Specialist employers on an E-3 visa?
Yes, but each employer change requires a new LCA and a new visa application. Your E-3 is employer-specific, so you can't transfer it to a new company the way some other visa categories allow. If you're already inside the U.S., you can start working for the new employer once the new E-3 is approved at the consulate or via a change of status petition with USCIS.
See which AI Specialist employers are hiring and sponsoring visas right now.
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