Full Linux machines in <50ms. Persistent runtime. Never sleep. Only pay for active compute. Backed by Y Combinator.
About the role
We’re looking for unusually high-potential engineers who want to learn how reliable systems are designed, built, broken, and improved. Think abstractions are useful because you understand what’s underneath them.
What they're looking for
- Think abstractions are useful because you understand what’s underneath them
- Enjoy figuring out how operating systems, networks, and distributed systems actually work
- Care about latency, throughput, memory usage, and system reliability
- Like debugging difficult problems and learning from them
- Think distributed systems are fun rather than frightening
- Read systems blogs or papers because you’re genuinely interested
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 abstractions are useful because you understand what’s...
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