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.