AI ML Platform Jobs in USA with Visa Sponsorship
AI/ML Platform engineers are among the most actively sponsored roles in the U.S. tech industry. Employers regularly file H-1B and O-1 petitions for this specialty, and the work squarely qualifies as a specialty occupation under USCIS standards. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsJob Description/Preferred Qualifications
Join our AI/ML engineering team to build the backbone that powers production AI. As an AI/ML Platform Engineering Lead, you’ll architect and scale our MLOps infrastructure, enabling secure, reliable, and fast deployment of machine learning models across cloud and air gapped environments. This is a hands-on leadership role where you’ll mentor engineers, collaborate with hardware teams, and deliver AI solutions that transform semiconductor manufacturing.
Why This Role Is Compelling
- Growth: You are empowered to make decisions to release product. Clear path for leadership and technical advancement in a fast-evolving AI domain with a strong and young team to help shape their careers.
- Impact: Ship AI solutions that directly reach customers and shape next-gen manufacturing.
What You’ll Do
- Design, deploy and scale AI/ML platforms for model training and inference.
- Implement CI/CD pipelines for models and data workflows, ensuring reproducibility and compliance.
- Develop tools and frameworks that empower ML engineers to move from prototype to production seamlessly.
- Collaborate with cross-functional teams—including hardware and software—to integrate AI into instruments and factory workflows.
- Establish observability and governance for model performance, drift detection, and reliability.
- Mentor engineers and champion best practices in platform engineering and MLOps.
What We’re Looking For
- Strong programming skills in Python; experience with ML frameworks (PyTorch, TensorFlow, Keras).
- Expertise in MLOps tools (MLflow, Kubeflow), container orchestration (Kubernetes, Docker), and infrastructure automation (Terraform).
- Experience deploying models in secure or disconnected environments (air gapped, on-prem).
- Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid architectures.
- Proven ability to lead technical design discussions and mentor engineering teams.
Minimum Qualifications
Requires a minimum of 5 years of related experience with a Bachelors degree, or 3 years of experience and a Masters Degree.
Job Description/Preferred Qualifications
Join our AI/ML engineering team to build the backbone that powers production AI. As an AI/ML Platform Engineering Lead, you’ll architect and scale our MLOps infrastructure, enabling secure, reliable, and fast deployment of machine learning models across cloud and air gapped environments. This is a hands-on leadership role where you’ll mentor engineers, collaborate with hardware teams, and deliver AI solutions that transform semiconductor manufacturing.
Why This Role Is Compelling
- Growth: You are empowered to make decisions to release product. Clear path for leadership and technical advancement in a fast-evolving AI domain with a strong and young team to help shape their careers.
- Impact: Ship AI solutions that directly reach customers and shape next-gen manufacturing.
What You’ll Do
- Design, deploy and scale AI/ML platforms for model training and inference.
- Implement CI/CD pipelines for models and data workflows, ensuring reproducibility and compliance.
- Develop tools and frameworks that empower ML engineers to move from prototype to production seamlessly.
- Collaborate with cross-functional teams—including hardware and software—to integrate AI into instruments and factory workflows.
- Establish observability and governance for model performance, drift detection, and reliability.
- Mentor engineers and champion best practices in platform engineering and MLOps.
What We’re Looking For
- Strong programming skills in Python; experience with ML frameworks (PyTorch, TensorFlow, Keras).
- Expertise in MLOps tools (MLflow, Kubeflow), container orchestration (Kubernetes, Docker), and infrastructure automation (Terraform).
- Experience deploying models in secure or disconnected environments (air gapped, on-prem).
- Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid architectures.
- Proven ability to lead technical design discussions and mentor engineering teams.
Minimum Qualifications
Requires a minimum of 5 years of related experience with a Bachelors degree, or 3 years of experience and a Masters Degree.
How to Get Visa Sponsorship in AI ML Platform
Frame your role as infrastructure, not research
AI/ML Platform is distinct from applied ML, you build the systems others train on. Emphasize distributed systems, MLOps pipelines, and compute orchestration in your resume. Visa officers and employers respond to infrastructure framing over vague 'AI' titles.
Target companies with established ML infrastructure teams
Large-scale tech firms and AI-native companies already have USCIS-approved H-1B specialty occupation classifications for platform engineering roles. Applying to companies with prior approval history significantly reduces petition risk and employer hesitation around sponsorship.
Clarify your degree field on every application
USCIS requires a degree in a directly related field, computer science, computer engineering, and electrical engineering qualify cleanly. If your degree is adjacent, document coursework in systems design or distributed computing to strengthen the specialty occupation argument.
Highlight specific platform technologies in your materials
Kubernetes, Ray, Kubeflow, Spark, and Triton inference server are concrete signals that distinguish platform engineers from generalist ML practitioners. Specificity in tooling helps employers justify the specialty occupation requirement to USCIS when petitioning.
Understand your OPT and cap-gap timeline before applying
If you're on F-1 OPT, H-1B cap season runs January through April for October start dates. Platform roles at cap-exempt universities or research labs allow year-round filing, worth targeting if your OPT timeline doesn't align with the annual lottery.
Document production-scale impact, not just model performance
Sponsoring employers need to justify a specialty occupation petition. Resume bullet points quantifying platform throughput, uptime improvements, or training cost reductions give immigration counsel concrete evidence that the role requires specialized technical expertise.
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Get Access To All JobsFrequently Asked Questions
Does an AI/ML Platform engineer role qualify as a specialty occupation for H-1B purposes?
Yes. AI/ML Platform engineering requires at least a bachelor's degree in computer science, computer engineering, or a closely related field, meeting USCIS's specialty occupation definition. The role involves designing distributed training infrastructure, ML pipelines, and serving systems that require theoretical and applied depth. Generalist or non-technical degrees are unlikely to satisfy the field-of-study requirement without substantial supporting documentation.
Which visa types are most common for AI/ML Platform engineers?
H-1B is the most common path, though it requires winning the annual lottery. O-1A is a realistic alternative for engineers with strong publication records, open-source contributions, or documented industry recognition. Australians can pursue the E-3, which has no lottery and far lower competition. Canadians and Mexicans may qualify under the TN visa's computer systems analyst category. Browse open roles on Migrate Mate filtered by visa type to identify which employers are actively sponsoring.
Do employers actually sponsor H-1B visas for platform engineering roles?
Yes, and frequently. Companies like Google, Meta, Amazon, Microsoft, and AI-native firms such as Databricks and Anyscale have substantial H-1B filing histories for ML infrastructure and platform roles. DOL disclosure data confirms platform engineering titles appear consistently across LCA filings. The key filter is employer size and existing immigration infrastructure; smaller startups may be willing but slower to initiate the process.
What degree do I need to get sponsored for an AI/ML Platform role?
A bachelor's degree or higher in computer science, computer engineering, electrical engineering, or a directly related technical field is the standard requirement. Degrees in mathematics or physics may qualify with strong systems-focused coursework. If your degree is in a less directly related field, three years of relevant professional experience can substitute for one year of education under USCIS equivalency standards, though this requires detailed documentation and an immigration attorney's support.
How competitive is the H-1B lottery for AI/ML Platform engineers?
In FY 2025, USCIS received approximately 442,000 registrations for 85,000 available slots, resulting in a selection rate around 25%. Engineers with a U.S. master's degree or higher enter a separate pool first, improving odds modestly. If you don't get selected, cap-exempt employers, universities, nonprofit research labs, and certain government entities, can file outside the lottery. TN, E-3, and O-1 visas bypass the cap entirely and are worth evaluating if lottery odds are a concern.
What is the prevailing wage requirement for sponsored AI ML Platform jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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