About the Role

Join a small engineering team at an AI company focused on reinforcement learning environments, model evaluation, and post-training data. You will tackle urgent, ambiguous technical challenges for AI labs and data vendors, while turning repeated deployment work into reusable tools.

What You'll Do

Own technical deployment requests from initial triage through resolution.

Diagnose ambiguous technical problems and clarify what needs to be done.

Build tools and one-off pipelines to address urgent customer and partner needs.

Coordinate with research, go-to-market, and other internal teams to unblock deployments.

Balance speed and quality, escalating when correctness or security requires extra care.

Document recurring issues and convert manual work into reusable tools and processes.

What We're Looking For

Two to four years of experience in applied research engineering, forward-deployed engineering, or a similar hands-on technical role.

Research engineering experience alongside customer-facing deployment work, including ownership of requests from triage to completion.

Proficiency in Python, Docker, and Linux, with strong debugging skills across code, data, and environments.

Experience with benchmarks and evaluations for reinforcement learning training data and AI agents, including assessing task realism, rubric reliability, and useful training trajectories.

Ability to build practical tools and pipelines, work directly with technical customers or vendors, and handle urgent production or deployment issues.

Strong independent judgment in ambiguous situations, clear communication across time zones, and experience in an early-stage startup environment.

Compensation & Benefits

Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.

Location

On-site in Singapore, Singapore.