About this role
About the RoleJoin a small engineering team at an early-stage AI evaluation infrastructure startup, working on urgent, ambiguous technical challenges for AI research organizations and data vendors. You will own deployments from initial triage through resolution, helping unblock critical work while turning recurring problems into reusable tools and processes.
What You'll DoDiagnose ambiguous technical problems, ask clarifying questions, and determine the work needed to resolve them.
Own technical deployment requests from triage to completion for external partners and internal teams.
Build tools and one-off pipelines to address urgent customer, vendor, or partner problems.
Coordinate with research and go-to-market teams to unblock deployments.
Balance speed with quality, escalating when correctness or security requires extra care.
Document recurring issues and automate repeated manual work into reusable tools or processes.
What We're Looking ForTwo to four years of experience in applied research engineering, forward-deployed engineering, or similar hands-on technical roles, with research engineering experience.
Proficiency in Python, Docker, and Linux, plus a background in a technical field.
Experience building or evaluating benchmarks and evaluations for reinforcement learning training data and AI agents, with sound judgment about task realism, rubric reliability, and useful training trajectories.
Strong debugging skills across code, data, and environments, including experience with urgent production or deployment issues.
Experience working directly with technical customers, vendors, or cross-functional teams, and delivering work independently amid ambiguity.
Early-stage startup experience, strong communication across time zones, and a commitment to careful, original technical work.
Compensation & BenefitsCompensation is USD 150,000 to USD 250,000 annually. Visa sponsorship is available.
LocationOn-site in Singapore, Singapore.