CPT AI Engineer Jobs
AI Engineer jobs on CPT let F-1 students apply machine learning, model training, and inference pipeline work directly to their degree program. Your DSO must authorize each CPT position before you start, and the role must connect to your enrolled coursework, not just your field of study.
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Are you someone who is passionate, motivated, and driven to make a difference? If so, MSA Safety is the perfect fit for your career.
At MSA, SAFETY is who we are AND it is what we do. We are a purpose-driven company committed to deploying innovation and technology to deliver on our Mission to help protect people and assets all around the world. We continue to be relentless in our pursuit of solving our customers' greatest problems so they can go home safe each and every day.
Are you in? Read on for more details about this particular role.
ABOUT THE ROLE:
We’re building an AI Platform that empowers users across business functions to connect with enterprise data and accomplish everything from intelligent search to agentic workflows for task automation and artifact generation. The platform is accelerating business processes and shaping new ways we serve and innovate for our customers, with growing use cases across frontline support, NPD engineering, and business development.
As an AI Engineer on this team, you’ll help design, build, and scale the systems behind this work. You’ll work across the stack: orchestrating LLMs and agents, integrating with enterprise data sources, deploying in the cloud, and iterating based on how real users actually use what we build.
We move fast, and we’re looking for someone who thrives in that environment: adaptable, quick to learn, and an excellent communicator who can turn ambiguity into clear direction and shipped work.
Responsibilities:
- Design and build AI-enabled applications and services powering intelligent search, agentic workflows, and artifact generation
- Develop and orchestrate agentic systems, including tool use, multi-step reasoning, and evaluation loops grounded in real-world feedback
- Deploy, monitor, and continuously improve models and AI services on AWS
- Partner with stakeholders across MSA business functions to translate real needs into tools that drive productive use
- Contribute to architectural discussions and help drive technical decisions across the team
- Write clean, maintainable, well-documented code and uphold strong engineering practices (Git, code review, CI/CD, testing)
QUALIFICATIONS
Required Education and Experience:
- Working towards achieving a Bachelor's / Master’s Degree in AI Engineering, Data Science, Computer Science, Statistics, Mathematics, Engineering or related quantitative discipline
- Experience building AI-enabled applications, ideally involving agentic workflows, tool orchestration, and evaluation
- Experience with MLOps practices, including model deployment, monitoring, and evaluation in a cloud environment (AWS preferred)
- Proficiency in Python; TypeScript is a plus
- Working experience with at least one major ML framework (PyTorch or TensorFlow)
- Solid understanding of transformer-based models, including multimodal architectures, and familiarity with parameter-efficient fine-tuning (e.g., LoRA, QLoRA) and model optimization techniques (quantization, pruning, distillation)
- Understanding of how software works across the stack and in the cloud, including containers, serverless functions, databases, and observability/telemetry
- Strong software engineering fundamentals and a track record of clean, well-tested code
- Adaptability and a fast pace, with the curiosity to pick up new tools and frameworks as the AI landscape evolves
- Excellent communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders
Preferred Education and Experience:
- Experience working with open-source models via Hugging Face and managed services such as AWS Bedrock and Bedrock AgentCore, as well as agent SDKs like Strands
- Experience working with enterprise ERP and CRM systems such as SAP and Salesforce
- Experience in an agile development environment
- Experience with Vision Transformers and/or CNNs
- Familiarity with SQL, ETL, and working with large datasets
Overview:
Are you someone who is passionate, motivated, and driven to make a difference? If so, MSA Safety is the perfect fit for your career.
At MSA, SAFETY is who we are AND it is what we do. We are a purpose-driven company committed to deploying innovation and technology to deliver on our Mission to help protect people and assets all around the world. We continue to be relentless in our pursuit of solving our customers' greatest problems so they can go home safe each and every day.
Are you in? Read on for more details about this particular role.
ABOUT THE ROLE:
We’re building an AI Platform that empowers users across business functions to connect with enterprise data and accomplish everything from intelligent search to agentic workflows for task automation and artifact generation. The platform is accelerating business processes and shaping new ways we serve and innovate for our customers, with growing use cases across frontline support, NPD engineering, and business development.
As an AI Engineer on this team, you’ll help design, build, and scale the systems behind this work. You’ll work across the stack: orchestrating LLMs and agents, integrating with enterprise data sources, deploying in the cloud, and iterating based on how real users actually use what we build.
We move fast, and we’re looking for someone who thrives in that environment: adaptable, quick to learn, and an excellent communicator who can turn ambiguity into clear direction and shipped work.
Responsibilities:
- Design and build AI-enabled applications and services powering intelligent search, agentic workflows, and artifact generation
- Develop and orchestrate agentic systems, including tool use, multi-step reasoning, and evaluation loops grounded in real-world feedback
- Deploy, monitor, and continuously improve models and AI services on AWS
- Partner with stakeholders across MSA business functions to translate real needs into tools that drive productive use
- Contribute to architectural discussions and help drive technical decisions across the team
- Write clean, maintainable, well-documented code and uphold strong engineering practices (Git, code review, CI/CD, testing)
QUALIFICATIONS
Required Education and Experience:
- Working towards achieving a Bachelor's / Master’s Degree in AI Engineering, Data Science, Computer Science, Statistics, Mathematics, Engineering or related quantitative discipline
- Experience building AI-enabled applications, ideally involving agentic workflows, tool orchestration, and evaluation
- Experience with MLOps practices, including model deployment, monitoring, and evaluation in a cloud environment (AWS preferred)
- Proficiency in Python; TypeScript is a plus
- Working experience with at least one major ML framework (PyTorch or TensorFlow)
- Solid understanding of transformer-based models, including multimodal architectures, and familiarity with parameter-efficient fine-tuning (e.g., LoRA, QLoRA) and model optimization techniques (quantization, pruning, distillation)
- Understanding of how software works across the stack and in the cloud, including containers, serverless functions, databases, and observability/telemetry
- Strong software engineering fundamentals and a track record of clean, well-tested code
- Adaptability and a fast pace, with the curiosity to pick up new tools and frameworks as the AI landscape evolves
- Excellent communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders
Preferred Education and Experience:
- Experience working with open-source models via Hugging Face and managed services such as AWS Bedrock and Bedrock AgentCore, as well as agent SDKs like Strands
- Experience working with enterprise ERP and CRM systems such as SAP and Salesforce
- Experience in an agile development environment
- Experience with Vision Transformers and/or CNNs
- Familiarity with SQL, ETL, and working with large datasets
See all 113+ CPT AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new CPT AI Engineer Jobs.
Get Access To All JobsAI Engineer CPT: Frequently Asked Questions
Does CPT for an AI Engineer role require the employer to file anything with USCIS?
No. CPT authorization is entirely school-driven. Your DSO updates your I-20 to reflect the authorized employer, start date, and end date. USCIS is not involved and no petition is filed. The employer only needs to verify your eligibility through E-Verify and onboard you with your updated I-20 as the work authorization document.
Can I do full-time CPT as an AI Engineer without affecting my OPT eligibility?
You can use full-time CPT for one year or less without losing OPT eligibility. If you accumulate more than 12 months of full-time CPT across your degree program, you lose OPT eligibility entirely. Part-time CPT, meaning fewer than 20 hours per week, doesn't count toward that limit regardless of duration.
How do I show my AI Engineer duties are integral to my curriculum?
Your DSO needs to connect specific job duties to a course you're enrolled in or a thesis requirement. For AI Engineer roles, duties like training neural networks, building inference pipelines, or deploying models typically align with graduate coursework in machine learning, deep learning, or computer science. A detailed offer letter with role responsibilities makes this connection easier to document.
What types of employers hire F-1 students on CPT for AI Engineer roles?
Technology companies, research labs, financial services firms, and health tech startups regularly hire F-1 students on CPT for AI Engineer positions. Migrate Mate lets you filter specifically for employers with Labor Condition Application filing history in AI and software roles, so you can focus your applications on companies already familiar with work authorization requirements.
Can I switch employers mid-CPT if I receive a better AI Engineer offer?
Yes, but each employer requires separate CPT authorization. Your DSO must issue a new I-20 reflecting the new employer before you begin work. You'll need a new offer letter and your DSO must again confirm the role is integral to your curriculum. Starting work at the new employer before your updated I-20 is issued would violate your F-1 status.