About the Role
Join a small engineering team at an early-stage AI infrastructure company focused on reinforcement learning environments, benchmarks, and model evaluation. You will tackle urgent, ambiguous technical challenges for AI research teams and data providers, helping unblock deployments while turning recurring problems into reusable tools.
What You'll Do
Diagnose ambiguous technical problems and clarify the underlying needs.
Own technical deployment requests from initial triage through completion.
Build tools and one-off pipelines to address urgent partner and customer challenges.
Coordinate with research and go-to-market teams to unblock deployments.
Balance fast turnaround with quality, correctness, and security.
Document recurring issues and automate 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 closely related hands-on technical role.
Research engineering experience alongside experience delivering technical deployments.
Proficiency with Python, Docker, and Linux environments.
Experience with benchmarks and evaluations for reinforcement learning training data or AI agents, including sound judgment about task realism, rubric reliability, and useful training trajectories.
Ability to debug across code, data, and environments, and to build practical tools and pipelines quickly.
Experience working directly with technical customers, vendors, or cross-functional teams, including ownership of urgent production or deployment issues.
Ability to work independently in ambiguous, fast-paced settings, with clear communication across time zones.
Compensation & Benefits
Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.