Job Description
Job DescriptionAbout the role
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.
You'll build the core technology our customers depend on. We're looking for a systems engineer who wants to understand where time and memory go, why a system fails, and what a better design would make possible. You enjoy following a problem through application code, the operating system, storage, and the network until you can explain it and improve it.
This role covers two areas: the control plane, which creates, schedules, and manages Machines, and our Rust virtual machine monitor (VMM), the software that runs each virtual machine. We are looking for depth in either area, with room for someone who spans both.
You'll work directly with our CTO and engineers, with substantial freedom to investigate and choose an approach. We want someone who takes pride in the craft, moves with urgency, and cares about the details other engineers will have to live with. You'll carry work from the first experiment through implementation, verification, rollout, and operation.
What you'll work on
Build the control plane. Implement the APIs and services that create, schedule, and manage Machines. Reason about concurrency, resource ownership, durable state, and recovery. Make the behavior understandable when a request is canceled, a process dies, or part of an operation fails.
Improve the Rust VMM and runtime. Work on virtualization, guest memory, devices, and Linux I/O. Make machine startup, execution, snapshot, and recovery behavior correct and measurable. Your focus can be here, in the control plane, or across both.
Find and remove performance costs. Profile startup and request latency, syscall overhead, allocation, scheduling, networking, and storage. Follow database and I/O costs when they explain the bottleneck. Build a small reproduction, establish a baseline, and measure changes under representative load and failure conditions.
Design secure interfaces. Build services and communication paths with clear ownership and explicit trust boundaries. Relevant experience includes HTTP servers, interprocess communication, network protocols, and interactions across privilege levels. Find security problems with concrete failure or attack paths, explain their impact, and verify the fix.
You'd be a good fit if
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You know Linux internals well enough to investigate below an API, and you enjoy learning the layers you have not worked in yet. You can explain memory use, concurrency, syscall costs, and failure behavior in code you have built.
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For control-plane work, show strong service implementation in Go, Rust, or a comparable systems language. For VMM work, we look for hands-on Rust and low-level systems experience. In either area, you can explain the choices you made around types, memory, ownership, concurrency, and useful abstractions.
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You have a record of learning, adapting, and shipping, with recent hands-on work you can explain. You notice useful work, act on it, seek feedback early, and improve the result. You can simplify a design, make a decision, and finish it.
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You are security-minded and precise about risk. You can point to an assumption others missed, show why it mattered, and distinguish a real vulnerability from a speculative concern.
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You communicate clearly and care about the reader. You can explain a difficult investigation, defend a design, engage with an objection, and help another engineer become effective. Technical writing, code reviews, design notes, and thoughtful project documentation are useful evidence.
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You use modern AI coding tools to amplify an already strong technical foundation and accelerate learning. You understand, test, and take responsibility for the resulting code. You stay open to better tools and change your approach when the evidence warrants it.
Additional depth we value
Depth in filesystems, storage engines, databases, or distributed systems can complement either focus. Formal specifications, model checking, or proofs are strong bonuses when you can explain what they established and how they changed the implementation. Interest in AI infrastructure and systems research is welcome. GPU infrastructure experience is an additional plus.
These are examples, not a checklist. We want exceptional depth in a relevant area, strong fundamentals, and the ability to learn the layers around it. Production, open-source, research, and independent work can all demonstrate that. A particular employer, degree, public following, or experience with every item above is not required.
Logistics
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Full-time and in person in San Francisco.
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Relocation support is available.
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We sponsor visas for exceptional talents.
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Competitive salary, bonus, and meaningful equity.
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Meals and office benefits are included.
Show us your work
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.
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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.
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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.
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Writing: Share one piece of writing you care about as a separate, required sample. Any medium or length is welcome. Tell us why you wrote it, who it was for, and what you wanted to communicate. Looking back, what works well and what would you change? We care about the quality of your thinking and writing, and your reflection on the work. Link it or paste a redacted excerpt. Explain your contribution 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.
Compensation Range: $120K - $250K