About the Role
This is a hands-on, end-to-end ownership role on a small, high-caliber engineering team building infrastructure for AI evaluation and reinforcement learning environments. You'll be the person who unblocks critical deployments for frontier AI labs and data vendors — diagnosing ambiguous problems fast, shipping solutions, and turning repeated firefighting into durable tooling. The work is urgent, impactful, and rarely fully prescribed.
What You'll Do
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Take the lead on diagnosing and resolving ambiguous technical problems as they arise.
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Own technical deployment requests from frontier AI labs and data vendors, from initial triage through to completion.
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Ask the right questions to clarify underspecified asks and identify what actually needs to be built.
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Build one-off tools and pipelines to solve urgent customer or partner problems quickly.
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Coordinate with research and go-to-market teams to keep deployments moving.
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Balance speed and quality under time pressure when the path forward isn't fully defined.
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Document recurring issues and convert repeated manual work into reusable tools and processes.
What We're Looking For
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2–4 years of experience in applied research engineering, forward-deployed engineering, or a closely related hands-on technical role.
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Proficiency in Python, Docker, and Linux environments.
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Experience working on benchmarks and evals — with solid judgment about task realism, rubric reliability, and trajectory quality for RL training.
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Strong debugging instincts across code, data, and environments.
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Proven ability to operate independently in ambiguous situations without a fully prescribed roadmap.
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Comfort working directly with technical customers, vendors, and cross-functional internal teams.
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Experience handling urgent production, customer, or deployment issues under pressure.
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Early-stage startup experience and the ability to move fast in a small, high-ownership environment.
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Strong written and verbal communication skills for async, cross-timezone collaboration.
Compensation & Benefits
Salary range: $150,000 – $250,000 USD annually. Visa sponsorship is available.
Location
On-site in San Francisco, CA, USA. Candidates based in or able to relocate to San Francisco are preferred. The role may also be based in Singapore.
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