About the Role
Join an engineering team at an early-stage AI evaluation infrastructure company, solving urgent technical challenges for AI research organizations and data partners. You will own deployments from initial diagnosis through implementation, helping unblock important work and turn recurring problems into reusable tools.
What You'll Do
Diagnose ambiguous technical problems, clarify requirements, and determine practical solutions.
Own deployment requests from triage through completion for external partners and internal teams.
Build tools and one-off pipelines to address urgent customer and partner needs.
Collaborate with research and go-to-market teams to unblock deployments.
Balance speed and quality while debugging issues across code, data, and technical environments.
Document recurring problems 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 closely related hands-on technical role.
Research engineering experience alongside forward-deployed or customer-facing engineering work.
Proficiency with Python, Docker, and Linux environments.
Experience developing benchmarks and evaluations for reinforcement learning training data and AI agents, with sound judgment about task realism, rubric reliability, and useful training trajectories.
Experience owning technical deployments, building tools or pipelines for urgent needs, and working directly with technical customers, vendors, or cross-functional teams.
Strong debugging, communication, and independent problem-solving skills, including experience handling urgent production or deployment issues.
Comfort working in an early-stage startup and making careful decisions in ambiguous, fast-moving situations.
Compensation & Benefits
Compensation is USD $100,000 to $170,000 annually. Visa sponsorship is available.
Location
This is an on-site role based in Singapore, Singapore.