Join a small engineering team at an AI/ML company focused on reinforcement learning environments, evaluations, and training data. You will solve urgent, ambiguous technical challenges for AI labs, data vendors, and internal teams, while turning repeated deployment work into reusable tools.
Diagnose ambiguous technical problems and clarify what needs to be done.
Own technical deployment requests from triage through completion.
Build tools and one-off pipelines to address urgent customer and partner needs.
Coordinate with research and go-to-market teams to unblock deployments.
Balance fast delivery with quality, correctness, and security.
Document recurring issues and automate manual work into reusable tools or processes.
Two to four years of experience in applied research engineering, forward-deployed engineering, or a similar hands-on technical role.
Research engineering experience alongside experience owning technical deployments.
Proficiency in Python, Docker, and Linux, with a technical educational background.
Experience with benchmarks and evaluations for reinforcement learning training data or AI agents, including sound judgment about task realism and rubric quality.
Strong debugging skills across code, data, and technical environments.
Ability to work independently through ambiguity, handle urgent production or deployment issues, and communicate effectively with technical customers, vendors, and cross-functional teams.
Experience at an early-stage startup and a track record of careful, original technical work.
Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.
On-site in Singapore, Singapore.