Applied AI Engineer Internships
Applied ai engineer internships give university students, recent graduates, and early-career switchers hands-on project experience building and deploying real AI systems, mentorship from working engineers, and, at many employers, a path toward a full-time offer. Openings are concentrated in {{top_industries_phrase}}, with Amazon, BRAIN, and Nuclear among the employers posting roles now.
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Our Mission
Rebuild how the world works, to make institutions work better for the people they serve.
About Brain Co.
Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.
Why Now
Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.
Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.
You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.
About the Role:
As an AI/ML Engineer Intern, you’ll work alongside experienced engineers and researchers to help design, build, and deploy machine learning systems that solve high-impact problems in healthcare, government, and energy.
This internship is designed for current undergraduate students, specifically juniors and seniors graduating no later than June 2028, who want hands-on experience applying modern AI techniques, especially large language models, to real-world challenges. You’ll gain exposure to the full ML lifecycle while receiving mentorship and ownership over meaningful projects.
What You’ll Do
Assist in designing and deploying LLM-powered applications to automate complex, real-world workflows
Build and improve data pipelines and support model training, evaluation, and optimization
Work with structured and unstructured data (e.g., text, documents, logs)
Help prepare models and systems for production deployment and monitoring
Collaborate closely with senior engineers, AI researchers, and product teams
Learn best practices through code reviews, design discussions, and hands-on mentorship
Gain exposure to customer-facing and real-world constraints, including working with public-sector institutions
You Might Be a Good Fit If You
Are a current undergraduate students, specifically juniors and seniors graduating no later than June 2028, pursuing a degree in Computer Science, Machine Learning, Data Science, or a related field
Have experience programming in Python
Have coursework or project experience in machine learning or AI
Have exposure to or interest in large language models and GenAI applications (e.g., agents, RAG, reasoning workflows)
Have used or are eager to learn frameworks such as PyTorch, JAX, or TensorFlow
Have strong fundamentals in data structures and algorithms
Are curious, proactive, and excited to learn quickly in a fast-paced environmentEnjoy owning problems end-to-end with guidance and support
Internship Details & Benefits
Dates: May 31, 2027 - Aug 6, 2027 or July 5, 2027 - September 10, 2027
Competitive internship compensation
Hands-on mentorship from experienced AI engineers and researchers
Opportunity to work on real production systems used globally
Potential return-offer consideration for future internships or full-time roles
Daily lunches (if onsite)
Our Mission
Rebuild how the world works, to make institutions work better for the people they serve.
About Brain Co.
Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.
Why Now
Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.
Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.
You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.
About the Role:
As an AI/ML Engineer Intern, you’ll work alongside experienced engineers and researchers to help design, build, and deploy machine learning systems that solve high-impact problems in healthcare, government, and energy.
This internship is designed for current undergraduate students, specifically juniors and seniors graduating no later than June 2028, who want hands-on experience applying modern AI techniques, especially large language models, to real-world challenges. You’ll gain exposure to the full ML lifecycle while receiving mentorship and ownership over meaningful projects.
What You’ll Do
Assist in designing and deploying LLM-powered applications to automate complex, real-world workflows
Build and improve data pipelines and support model training, evaluation, and optimization
Work with structured and unstructured data (e.g., text, documents, logs)
Help prepare models and systems for production deployment and monitoring
Collaborate closely with senior engineers, AI researchers, and product teams
Learn best practices through code reviews, design discussions, and hands-on mentorship
Gain exposure to customer-facing and real-world constraints, including working with public-sector institutions
You Might Be a Good Fit If You
Are a current undergraduate students, specifically juniors and seniors graduating no later than June 2028, pursuing a degree in Computer Science, Machine Learning, Data Science, or a related field
Have experience programming in Python
Have coursework or project experience in machine learning or AI
Have exposure to or interest in large language models and GenAI applications (e.g., agents, RAG, reasoning workflows)
Have used or are eager to learn frameworks such as PyTorch, JAX, or TensorFlow
Have strong fundamentals in data structures and algorithms
Are curious, proactive, and excited to learn quickly in a fast-paced environmentEnjoy owning problems end-to-end with guidance and support
Internship Details & Benefits
Dates: May 31, 2027 - Aug 6, 2027 or July 5, 2027 - September 10, 2027
Competitive internship compensation
Hands-on mentorship from experienced AI engineers and researchers
Opportunity to work on real production systems used globally
Potential return-offer consideration for future internships or full-time roles
Daily lunches (if onsite)
Applied AI Engineer Internship Market
Who's Hiring
Tips for Your Applied AI Engineer Internship Search
Apply in fall for the following summer
Large technology and enterprise employers open summer applied ai engineer internship recruiting as early as August and September. If you wait until spring, many structured cohorts are already full. Set a calendar reminder to start applications in the fall semester, even if start dates feel far away.
Build a public portfolio before you apply
For applied ai engineer intern candidates, a linked code repository or project page is the artifact that gives recruiters something concrete to evaluate. Build two or three complete projects using real frameworks, PyTorch, LangChain, Hugging Face, document what you built and why, and make sure every link in your resume opens without errors.
Work your campus network and apply directly at the same time
Career fairs surface structured programs tied to your university, and professors or career center staff often know which employers recruit from your school before roles post publicly. Apply directly to companies running smaller cohorts alongside campus activity so you reach employers who never visit your campus at all.
Practice your technical screen out loud before applying
Applied ai engineer intern screens typically combine a coding assessment on algorithms and data structures with applied ML questions about model selection, evaluation, and trade-offs. Practice solving problems out loud and explaining your reasoning at each step, because interviewers weigh how you think through a problem as much as the final answer you reach.
Target structured AI internship and residency programs early
Larger technology companies run cohort-based AI internship and residency programs specifically designed to train people new to the field. These programs recruit early, fill fast, and often carry a higher conversion rate than ad-hoc intern placements. Identify the ones that fit your background and apply in the first wave of their recruiting cycle.
Set your work-type filter before you start
On-site roles are 50% of the applied ai engineer internships listed here. Decide what you can realistically commit to before you start searching, then filter by location and work type so you spend your time on roles you can actually accept rather than sorting through listings that don't fit your situation.
Applied AI Engineer Internships: Frequently Asked Questions
How do I get an applied ai engineer internship?
Lead with coursework, personal projects, and a portfolio rather than work history, hiring teams expect limited experience at the intern level. For applied ai engineer candidates, the concrete artifact recruiters want to assess is linked code or a public repository showing you've built and shipped something with real AI tools. Combine direct applications with campus career fairs, where recruiters often move faster for students they meet in person.
Can an applied ai engineer internship turn into a full-time job?
Many employers extend return offers to strong interns, but conversion is never guaranteed. What actually drives it for applied ai engineer interns is performance on real project work, whether the team has open headcount when your internship ends, and how early you signal interest in returning. Position yourself by delivering on your project scope and asking about the return-offer process before your internship concludes.
When should I apply for applied ai engineer internships?
Earlier than most candidates expect. Large technology and enterprise employers open summer internship recruiting the preceding fall, meaning cohorts can fill months before the start date. Smaller companies and co-op programs post closer to when roles begin, so openings appear year-round. Checking listings regularly rather than waiting for a single season gives you the widest window.
Are applied ai engineer internships paid?
Most professional applied ai engineer internships in the United States are paid. Compensation varies by company size, industry, and location, and listings show it where the employer chooses to disclose it. Unpaid internships do exist, typically at early-stage startups or nonprofits, so read each listing carefully before applying.
What should an applied ai engineer internship resume include?
Lead with projects, not work history: two or three complete, documented projects naming the models, frameworks, and tools you used, with linked code or a public repository recruiters can actually open. Add relevant coursework, machine learning, systems programming, data engineering, and any competition results or research contributions. Keep everything to one page.
Are there remote applied ai engineer internships?
Yes. Remote and hybrid roles make up 50% of the applied ai engineer internship listings here, with the rest on-site. Remote cohorts fill fast because they attract candidates from across the country, so apply early and filter by work type to see them before seats close.
What is an AI residency or research internship program?
AI residency and research internship programs are structured cohorts at larger technology companies designed to give candidates new to applied AI a full project cycle under close mentorship from research or engineering teams. They target recent graduates and career switchers, recruit early, and are competitive. Identify programs that match your background and apply in the first wave of their recruiting cycle.
Can international students get applied ai engineer internships?
Yes. F-1 students can intern through CPT while enrolled or through OPT work authorization after finishing a degree, and the employer does not have to file anything for either, so many companies are open to international interns. Confirm your eligibility and timing with your university's international student office before accepting an offer.
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