Research Engineer, Benchmarks

ABOUT THE ROLE Join a small, technical team working on AI evaluation and reinforcement learning infrastructure. You will design and build rigorous benchmarks for assessing AI agents on realistic, domain-specific workflows, helping research and engineering teams understand how well agents perform in practice. 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 practical tasks and evaluation criteria. - Build reliable infrastructure to run models and agents against benchmark tasks at scale. - Develop metrics and analyses to assess benchmark difficulty, reliability, and failure modes. - Validate benchmark results against real-world evaluations and user needs. - Write clear technical documentation and reports that explain methods and results. WHAT WE'RE LOOKING FOR - Two to four years of experience in software engineering, machine learning engineering, or research, including at least two years building AI benchmarks, evaluation infrastructure, or agent environments. - Hands-on experience designing and running evaluations or benchmark environments for AI agents or large language models. - Strong proficiency with Python, Docker, and Linux, including building and operating reliable infrastructure. - Experience developing metrics, statistical analyses, or validation studies for evaluation systems. - Experience collaborating with subject-matter experts and understanding workflows across technical or business domains. - Strong technical writing, careful attention to detail, and the ability to work independently in an early-stage, fast-moving environment. - Research publications or technical writing on benchmarking, model evaluation, or failure modes are beneficial. Experience with reinforcement learning pipelines or public benchmark projects is also useful. COMPENSATION & BENEFITS Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available. LOCATION On-site in Singapore, Singapore.