AI Internships and Graduate Programs
Summer internships at foundation labs, year-round co-ops at AI-native products, structured graduate programs at the AI infrastructure layer. All from the same hand-curated company list as the rest of /jobs/.
A few things that help when applying.
- Application windows are short and predictable. Foundation labs run summer-internship hiring from October through January for the following summer. Apply early — slots fill weeks before stated deadlines.
- A small reproducible project beats a strong CV. A working MCP server, a written-up local-LLM benchmark, an open-source contribution to an AI tool — these signal you can do the work. AI internships hire for that signal.
- Return-offer rates are unusually high. Most AI-native companies convert internships to full-time at 70-90%. An internship is often the cleanest route into the company you want to work for full time.
- Visa support is often pre-cleared at internship grade. Major foundation labs handle visa sponsorship for international interns as standard. Worth checking the specific posting; it's not always documented up front.
Tap a chip to jump to a category, or type to search.
Live internships, across categories.
New to AI work? Start with these.
Six pieces of orientation. Most AI-company job specs assume you've done this kind of hands-on work already. If you haven't, an afternoon with one of these is the cheapest way to close the gap.
Claude Desktop, from zero.
The agentic-AI assistant most of the people you'd be working alongside use every day. Install, configure, first useful prompts.
What MCPs areThe best MCPs for Claude Desktop.
MCP servers extend an AI assistant with tools and data. The catalogue most teams use. Useful technical context for any AI-engineering role.
Code with AIClaude Code, the complete beginners' guide.
The CLI for AI-paired development. Required reading if you're applying for any engineering role that mentions agents, or any role full stop.
Run a local modelHow to set up LM Studio.
Running a model on your own machine teaches you more about how AI products work in three hours than a year of using ChatGPT will.
The hardware realityBeginner's guide to AI hardware.
What the infrastructure under the model actually looks like. Useful context for infrastructure, applied-AI and hardware roles.
Browse the stackMCP catalogue.
Eleven MCP servers Houtini maintains or recommends. Each detail page describes a real piece of working AI infrastructure.