AI Platform Engineer Jobs for OPT Students
AI Platform Engineer jobs are among the most OPT-friendly roles in tech right now, with strong demand from employers already set up to sponsor H-1B visas. Most positions require a master's degree in computer science or a related field, which aligns well with the STEM OPT extension that gives you 36 months of authorized work.
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Get Access To All JobsINTRODUCTION
We are seeking an AI Platform Engineer to help design, build, and scale an enterprise AI platform that enables secure, governed machine learning and generative AI capabilities across the organization. In this role, you will partner with data science, product, cloud, and security teams to design, deploy, and optimize AI workloads while owning platform capabilities end-to-end. The position blends software engineering, cloud architecture, data engineering, and applied machine learning, helping teams build and operate AI solutions using technologies such as AWS, Databricks, Spark, and Python.
Responsibilities:
- Build and maintain large-scale Spark pipelines for data preparation, feature engineering, and model inference.
- Develop production-grade applications using Python, SQL, and modern software engineering practices.
- Design and build REST APIs and backend services supporting AI and machine learning workloads.
- Create shared frameworks, tools, and platform components to standardize and accelerate AI development.
- Deploy and operationalize machine learning models in partnership with data science teams.
- Implement secure and scalable cloud architectures on AWS, including services such as S3, Lambda, and IAM.
- Improve platform reliability, observability, and performance across AI workloads.
- Apply security best practices, including IAM design, data protection, and secrets management.
- Contribute to CI/CD pipelines and infrastructure-as-code using tools such as Terraform.
- Support GenAI initiatives, including prompt engineering and retrieval-augmented generation (RAG).
- Monitor production systems, troubleshoot issues, and optimize cost and performance.
Experience:
- Experience building large-scale data pipelines with Spark or PySpark.
- Strong programming experience in Python and SQL.
- Experience designing and integrating REST APIs and backend services.
- Hands-on experience with AWS services such as S3, Lambda, and IAM.
- Experience supporting the machine learning lifecycle, including model training, deployment, and monitoring.
- Strong understanding of software engineering best practices, including CI/CD, testing, and version control.
- Experience with Databricks, including tools such as Delta Lake or MLflow.
- Familiarity with GenAI technologies, including prompt engineering or RAG patterns.
- Experience with Terraform or infrastructure-as-code tools is a plus.
INTRODUCTION
We are seeking an AI Platform Engineer to help design, build, and scale an enterprise AI platform that enables secure, governed machine learning and generative AI capabilities across the organization. In this role, you will partner with data science, product, cloud, and security teams to design, deploy, and optimize AI workloads while owning platform capabilities end-to-end. The position blends software engineering, cloud architecture, data engineering, and applied machine learning, helping teams build and operate AI solutions using technologies such as AWS, Databricks, Spark, and Python.
Responsibilities:
- Build and maintain large-scale Spark pipelines for data preparation, feature engineering, and model inference.
- Develop production-grade applications using Python, SQL, and modern software engineering practices.
- Design and build REST APIs and backend services supporting AI and machine learning workloads.
- Create shared frameworks, tools, and platform components to standardize and accelerate AI development.
- Deploy and operationalize machine learning models in partnership with data science teams.
- Implement secure and scalable cloud architectures on AWS, including services such as S3, Lambda, and IAM.
- Improve platform reliability, observability, and performance across AI workloads.
- Apply security best practices, including IAM design, data protection, and secrets management.
- Contribute to CI/CD pipelines and infrastructure-as-code using tools such as Terraform.
- Support GenAI initiatives, including prompt engineering and retrieval-augmented generation (RAG).
- Monitor production systems, troubleshoot issues, and optimize cost and performance.
Experience:
- Experience building large-scale data pipelines with Spark or PySpark.
- Strong programming experience in Python and SQL.
- Experience designing and integrating REST APIs and backend services.
- Hands-on experience with AWS services such as S3, Lambda, and IAM.
- Experience supporting the machine learning lifecycle, including model training, deployment, and monitoring.
- Strong understanding of software engineering best practices, including CI/CD, testing, and version control.
- Experience with Databricks, including tools such as Delta Lake or MLflow.
- Familiarity with GenAI technologies, including prompt engineering or RAG patterns.
- Experience with Terraform or infrastructure-as-code tools is a plus.
How to Get Visa Sponsorship as an AI Platform Engineer
Emphasize your ML infrastructure experience up front
Hiring managers for AI Platform roles care most about experience with model serving, MLflow, Kubeflow, or similar tooling. Lead with specific systems you have built or maintained, not just the languages or frameworks you know.
Get your STEM OPT extension filed before the job search
Confirm your I-983 training plan is in order and your extension EAD has been applied for before you start interviewing. Employers will ask about your timeline, and a concrete answer builds confidence that hiring you carries no immediate risk.
Clarify the role qualifies as a specialty occupation
AI Platform Engineer positions almost universally require a bachelor's degree or higher in a specific technical field, which satisfies the specialty occupation standard. Confirm this with your DSO so you can speak to it confidently when the topic arises with employers.
Use Migrate Mate to find OPT-friendly AI Platform roles
Migrate Mate filters for employers who are actively open to OPT candidates, so you spend less time cold-applying to companies that will reject you at the visa question. Browse current AI Platform Engineer listings to shortlist realistic targets before you reach out.
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Get Access To All JobsFrequently Asked Questions
Do AI Platform Engineer jobs qualify for the STEM OPT extension?
Yes, in most cases. AI Platform Engineer roles fall under CIP codes in computer science or electrical engineering, which are on the STEM Designated Degree Program list. Your degree field, not the job title, determines STEM OPT eligibility, so confirm with your DSO that your program qualifies. Once confirmed, you get 24 additional months on top of your initial 12-month OPT period.
How does the practical training requirement work for AI Platform Engineer positions?
Your job must be directly related to your degree field. For AI Platform Engineers, roles involving model deployment, infrastructure automation, distributed systems, or data pipeline architecture almost always satisfy this requirement given their connection to computer science and engineering coursework. Document this connection carefully in your I-983 training plan, which your employer must sign and your DSO must approve before your STEM OPT extension is granted.
Will employers sponsor an H-1B visa after my OPT period ends?
Many do, but it varies by company size, budget, and hiring philosophy. Large tech companies and well-funded AI startups are the most consistent sponsors because they have legal teams set up to handle immigration. AI Platform Engineer is a high-demand, specialized role, which strengthens your negotiating position. Start the H-1B conversation early in the hiring process rather than after an offer is made.
Can I work as a contractor or on a project basis while on OPT?
Yes, but with conditions. OPT allows self-employment and contract work as long as the work is directly related to your degree. For AI Platform Engineers, contract engagements in machine learning infrastructure or cloud platform development typically qualify. You must work at least 20 hours per week to remain in valid OPT status, and unemployment gaps beyond 90 days cumulatively can jeopardize your authorization.
Where can I find AI Platform Engineer jobs that accept OPT candidates?
Migrate Mate is built specifically for this. The platform surfaces AI Platform Engineer roles from employers who are open to OPT candidates and have a track record of sponsoring visas, so you can filter out companies that will reject your application at the authorization step. Browse current listings on Migrate Mate to identify realistic targets based on your graduation date and OPT timeline.
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