dedalus-labs · San Francisco ·
Build and debug distributed infrastructure for AI agents, working on storage, orchestration, and scheduling systems in Rust/Go while learning how reliable systems are designed and improved.
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Dedalus Labs builds persistent computers for AI agents. Our flagship product, Dedalus Machines, gives agents an isolated environment where they can run software, keep files and state, and work over time.
We're looking for someone who notices a slow build, a repeated manual step, or a service that fails in a way nobody can explain, and wants to make it better. You'll learn how our infrastructure is built and operated by owning a useful improvement with the team.
This is a paid, full-time, approximately three-month internship in San Francisco. Applications are open throughout the year, with start dates agreed individually. You'll work alongside Dedalus engineers on a scoped project the team can use, with direct feedback on your implementation and decisions.
We want evidence that you can learn something difficult, finish a working version, and improve it when the first approach fails. You do not need prior production ownership. You should already have a project you understand well enough to explain its hardest bug, its limits, and your personal contribution.
A build, test, or deployment improvement. Trace where the time goes, identify repeated work or a reliability problem, and verify the change against the same workload.
A provisioning or developer-tooling workflow that another engineer can run and troubleshoot from its documentation.
A scoped scheduling, storage, or service-recovery improvement, with tests for interrupted work and partial failure.
Diagnostics that connect a failed operation to the relevant logs, metrics, and resource state, followed by a fix for the underlying problem.
Your project will have an agreed scope and completion criteria. The outcome should be usable by the team, with tests, documentation, and a clear account of its limitations.
You have completed a meaningful programming project in Go, Rust, C, C++, or a similar language. You can explain its design, inspect its behavior on Linux, and investigate a failure. Experience with CI/CD, containers, Kubernetes, cloud infrastructure, networking, or infrastructure as code is useful.
Show us a tool someone used, a service you operated, a difficult bug you reproduced, or an experiment that led to a working improvement. Research and coursework are welcome too. Tell us what you personally implemented, including any decisions or extensions beyond the starting instructions.
When you get stuck, you narrow the problem, read the relevant source or documentation, and try an experiment that can teach you something. You ask for help with the evidence you've collected and explain what you need to understand next. You act on feedback and keep ownership of the result.
You use AI coding tools where they help. You must be able to explain the resulting code, test its behavior, and correct it when it is wrong. We care about your judgment and understanding throughout the work.
We evaluate the work relative to your experience and opportunities. A degree, a particular employer, or owning hardware is not a prerequisite. Be specific about what you have already learned and where you want to go deeper.
You want to configure tools without understanding or investigating the software they run.
You need every next step supplied before trying a small experiment or asking a focused question.
You declare an improvement without checking whether another engineer can use it and whether the result is measurable.
Rolling applications throughout the year.
Approximately three months, with exact dates agreed individually.
Paid, full-time, and five days per week in person in San Francisco.
Meals and office benefits included.
Relocation support may be available.
Visa support may be considered depending on the candidate and circumstances.
Possible consideration for full-time employment, without a guarantee of conversion.
Use your application to show us one thing you built and one difficult problem you investigated. They can come from the same project. Choose work you already have. We are not asking you to build a new project for this application.
Work: Show the code, demo, design, or result. Explain what you personally owned, what you reused, and one decision that made the result better or simpler.
Investigation: Describe the symptom, your first explanation, the evidence that changed your thinking, and how you established the result. Include the workload or users involved and any important limitations.
Writing: Share one piece of your best writing as a separate, required sample. Simple and succinct is welcome. Choose work that shows your thinking and your voice in a professional or similarly thoughtful context: a strong README, design note, blog post, postmortem, proposal, or essay. A serious, self-contained Reddit post is fine. Tweets, Twitter/X threads, and short social posts do not count. Link it or paste a redacted excerpt. Tell us the intended audience, what you wrote, why you chose it, and any coauthors or AI assistance.
Work from employment, open source, research, coursework, or independent projects is welcome. Public source code is optional. A redacted excerpt or a concrete account of private work is fine. Keep confidential information out of your application.
Tell us which problem in this role you want to own and why. If your strongest evidence is easy to miss on a resume, point us to it. An existing demo or short screen recording is welcome, and video is optional.
Internship pay is $45-$50 per hour. The monthly range shown above is an approximate equivalent of $7,800-$8,667 at 40 hours per week, averaged over 52 weeks per year. Actual pay is based on hours worked.
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