Applied AI Deployment Engineer for Frontier Labs

Hud; Singapore; Remote; SGD 128,000 - 173,000; Full time

Benefits offered by this job

Unlimited tokens for AI tools

Competitive compensation

Remote-friendly

Visa sponsorship

Job summary

HUD is seeking an Applied Research Engineer to own implementation of data tooling for frontier AI labs and data vendors. You will diagnose ambiguous problems, run evals, and build pipelines to move fast while keeping quality.

You will work with research and GTM teams, balance speed and accuracy, and help deploy solutions across global time zones. Remote-friendly startup culture with strong funding and a focus on scalable data infrastructure.

Qualifications

• Core engineering experience, preferably in forward deployed or customer success contexts.
• Experience working on benchmarks and evals; ability to reason about task realism, rubric reliability, env usability, and RL training trajectories.
• Strong debugging instincts across code, data, and environments.
• Ability to operate independently in ambiguous situations without a fully prescribed roadmap.
• Strong judgment on when to move fast, when to elevate, and when accuracy or security requires extra care.

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.

Skills

Core engineering

Benchmarks & evals

Debugging

Independent work

Communication

Tools

-

Job description

HUD is seeking an Applied Research Engineer to own implementation of data tooling for frontier AI labs and data vendors. You will diagnose ambiguous problems, run evals, and build pipelines to move fast while keeping quality.

You will work with research and GTM teams, balance speed and accuracy, and help deploy solutions across global time zones. Remote-friendly startup culture with strong funding and a focus on scalable data infrastructure.