Quick Overview
Job Description
About the Role
This is a hands-on engineering role at the intersection of applied research and customer deployment, sitting within a small, high-caliber team building infrastructure for RL environments and AI evaluation. You'll own end-to-end resolution of urgent, ambiguous technical challenges for frontier AI labs and data vendors — turning repeated firefighting into durable, reusable tooling.
What You'll Do
Take the lead on diagnosing and resolving ambiguous technical problems from triage through to completion.
Own technical deployment requests from frontier AI labs, data vendors, and internal teams.
Ask the right questions to clarify underspecified asks and identify what actually needs to be done.
Build one-off tools and pipelines to solve urgent customer or partner problems quickly.
Coordinate with research and go-to-market teams to unblock critical deployments.
Balance speed and quality when customers need fast turnaround and the path isn't fully defined.
Document recurring issues and convert repeated manual work into reusable tools or processes.
What We're Looking For
2–4 years of experience in applied research engineering, forward-deployed engineering, or a closely related hands-on technical role.
Strong generalist AI engineering skills with a demonstrated ability to move quickly.
Proficiency in Python, Docker, and Linux environments.
Experience working on benchmarks and evals, with sound judgment about what makes a task realistic, a rubric reliable, and a trajectory useful for RL training.
Strong debugging instincts across code, data, and environments.
Proven ability to operate independently in ambiguous situations without a fully prescribed roadmap.
Comfort working directly with technical customers, vendors, or cross-functional internal teams.
Experience handling urgent production, customer, or deployment issues under time pressure.
Early-stage startup experience and comfort in fast-paced, self-directed environments.
Strong communication skills for remote collaboration across time zones.
Compensation & Benefits
Salary range: $150,000–$250,000 USD annually. Visa sponsorship is available.
Location
On-site in San Francisco, CA, USA. A second office is available in Singapore.
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