Full Linux machines in <50ms. Persistent runtime. Never sleep. Only pay for active compute. Backed by Y Combinator.
About the role
Depending on your strengths and the company’s needs, you may contribute to: Distributed infrastructure for large-scale AI agent workloads.
What they're looking for
- Think distributed systems are one of computer science’s most beautiful subjects
- Want to understand why systems fail—not merely how to make the happy path work
- Have built something technically difficult relative to your experience
- Can explain the hardest part of a project, what failed, and what you personally contributed
- Care about consistency, fault tolerance, concurrency, latency, and system correctness
- Enjoy learning how operating systems, storage engines, schedulers, networks, and runtimes work
More about this role
Dedalus Labs is an AI research neolab building infrastructure for AI agents.
We’re building the persistent compute layer that powers the next generation of autonomous software. Our platform spans distributed storage, virtualization, orchestration, networking, scheduling, and runtime infrastructure for long-running AI agents.
We’re looking for unusually high-potential engineers who want to learn how reliable systems are designed, built, broken, and improved.
This is a paid, full-time, approximately three-month internship based in San Francisco.
Applications remain open on a rolling, year-round basis. When we meet an exceptional or unusually high-slope engineer, we can invite them to join the team for a season.
You’ll work directly alongside Dedalus engineers on real infrastructure, not a disconnected intern project. You may shadow experienced engineers, but you’ll also be expected to take ownership, write production-quality code, investigate difficult problems, and explain your decisions.
Interns who demonstrate exceptional technical ability, judgment, ownership, and mutual fit may be considered for full-time roles.
Think distributed systems are one of computer science’s most...
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