Research Engineer, Benchmarks

ABOUT THE ROLE Join a small technical research and engineering team building benchmarks for evaluating AI agents on realistic, domain-specific workflows. You will own the design and implementation of rigorous evaluations that help technical teams understand how agents perform in real-world tasks. WHAT YOU'LL DO - Design, implement, and maintain benchmarks for evaluating AI agents on domain-specific tasks. - Work with subject-matter experts to translate real workflows into benchmark tasks and evaluation criteria. - Build and operate reliable infrastructure for running models and agents against tasks at scale. - Develop metrics and analyses to assess benchmark difficulty, reliability, and failure modes. - Validate whether benchmark results align with real-world performance and technical user needs. - Write clear documentation and reports for research and engineering audiences. WHAT WE'RE LOOKING FOR - Two to four years of experience in research engineering, machine learning engineering, or a related technical role, including at least two years building AI benchmarks, evaluation infrastructure, or agent environments. - Strong Python skills and practical experience with Docker and Linux. - Experience designing, implementing, and running benchmarks or evaluation environments for AI agents or large language models. - Experience collaborating with subject-matter experts and analyzing workflows across technical or business domains. - Experience developing metrics, statistical analyses, or validation studies for evaluations. - Strong technical writing, attention to detail, and ability to work independently in an early-stage environment. - A technical educational background; experience with reinforcement learning pipelines, published evaluation work, or widely used benchmarks is a plus. COMPENSATION & BENEFITS Salary range: USD 150,000 to 250,000 annually. Visa sponsorship is available. LOCATION On-site in Singapore, Singapore.