Dedalus Labs, Inc., San Francisco
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 improve the internal platform engineers use to build, test, release, and understand our software. This means GitHub Actions, build systems, release pipelines, and observability: collecting and connecting logs, metrics, traces, and errors so we can follow an operation across the platform and turn failures or regressions into specific fixes.
Our open-source tooling includes Bessemer (BSMR) https://github.com/dedalus-labs/bsmr, our build system, and Hollywood https://github.com/dedalus-labs/hollywood, which generates GitHub Actions from typed TypeScript definitions and runs actions locally.
You can write and debug software in Python, TypeScript, Go, Rust, or a similar language, and work comfortably with Git and Linux. Show us a CI workflow, release pipeline, developer tool, or observability project you built or improved. Coursework, research, open source, and independent projects count.
Experience with GitHub Actions, build systems, release automation, or logs and observability is especially useful. Grafana, Datadog, Sentry, OpenTelemetry, and similar tools are relevant. Explain how you used the data to diagnose a problem or improve a decision. Containers, Kubernetes, and infrastructure as code are useful supporting skills.
Experience at a big tech company or on another large, fast-moving codebase is a plus, not a requirement. We value what it taught you about code review, shared tooling, release discipline, and making changes other engineers can trust.
You understand when to use unit, integration, end-to-end, and property-based tests, and what each can and cannot establish. You choose efficient ways to verify a change, test invariants and failure cases, and make failures reproducible. Experience with formal verification or model checking is a plus.
When stuck, you narrow the problem, read source or documentation, and run an informative experiment. You ask for help with evidence, act on feedback, and finish the work.
You can use AI tools. You must understand, test, and correct the code you submit.
We evaluate your work relative to your experience and opportunities. A degree or particular employer is not required.
Finish with tested changes, documentation, and evidence that the workflow is faster, more reliable, or easier to diagnose.
40 hours per week, five days onsite in San Francisco. Meals and office benefits included. Relocation and visa support may be considered individually. Strong interns may be considered for full-time roles.
Show us a build or release workflow, developer tool, or observability project you improved, and a difficult problem you investigated. They can come from the same project. Use existing work.
Employment, open source, research, coursework, and independent projects all count. Links to your technical work or existing demos are optional but highly recommended so we can evaluate your body of work. Redacted excerpts are welcome for private work.
Tell us which problem in this role you want to own and why.
This is an evergreen opening. We review applications on an ongoing basis. Internships and co-ops last 3-9 months, depending on your school and co-op program.
Show us that you can learn something difficult, finish a working version, and improve it when the first approach fails. Prior production ownership is not required. You should be able to explain your project’s hardest bug, limits, and your contribution.
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Source: the Dedalus Labs, Inc. Ashby job board. We last checked this job 7 h ago. We first saw it 5 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.