← All roles

Forward Deployed Research Engineer

hud
Apply on company site
Hybrid (San Francisco / Singapore)$105k - $180kFull-timePosted 3mo ago

About the role

Applied role at HUD building reliable, fair and open infrastructure for AI data. The role focuses on owning deployment-related requests, diagnosing ambiguous problems, and delivering fast, high-quality solutions in collaboration with frontier AI labs, data vendors, and internal teams.

Responsibilities

  • Own technical deployment requests from frontier AI labs, data vendors, and internal teams from triage to completion
  • Ask the right questions to clarify ambiguous asks and identify what actually needs to be done
  • Build tools and one-off pipelines to solve urgent customer or partner problems
  • Coordinate with research and GTM teams to unblock deployments
  • Balance speed and quality in situations where customers need fast turnaround and the path is not fully specified
  • Document recurring issues and turn repeated manual work into reusable tools or processes

Qualifications

  • Core engineering experience, preferably in a forward deployed or customer success context
  • Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training
  • Strong debugging instincts across code, data, and environments
  • Demonstrated ability to operate independently in ambiguous situations without a fully prescribed roadmap
  • Strong judgment about when to move fast, when to escalate, and when correctness or security requires extra care
  • Comfort working directly with technical customers, vendors, or cross-functional internal teams

Skills

Required:Engineering fundamentalsBenchmarking and evaluationDebugging across code, data, and environmentsIndependent operation in ambiguityCustomer-facing collaboration
Last updated Oct 21, 2026. Interested? Apply on the company site.
hud logo

About hud

Platform for building RL environments and evals

HUD (YC W25) is developing agentic evals and RL environments for Computer Use Agents (CUAs) that browse the web for frontier AI labs. Our CUA Evals framework is the first comprehensive evaluation tool for CUAs. People don't actually know if AI agents are working reliably. To make AI agents work in the real world, we need detailed evals for a huge range of tasks. We're backed by Y Combinator, and work closely with frontier AI labs to provide agent evaluation and training infrastructure at scale.

artificial-intelligencereinforcement-learning
Company profileWebsite

More open roles at hud