Source-listed Job

Mid-Level Research Engineer, Benchmarks

ABOUT THE ROLE

Job Source description available
Clera Singapore Source published Oct 12, 2026 Source retrieved Oct 12, 2026
Source: Clera (ashby) · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
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EmploymentFull-time

Overview

ABOUT THE ROLE

Full job description

ABOUT THE ROLE Join a small, technical team at an early-stage AI evaluation infrastructure startup building benchmarks for frontier AI agents. You will own the design and implementation of rigorous evaluations for realistic, domain-specific workflows, helping technical teams understand how agent performance translates to practical settings. WHAT YOU'LL DO

  • Design, implement, and maintain benchmarks for evaluating frontier AI agents on domain-specific tasks.
  • Collaborate with subject-matter experts to turn real workflows into realistic benchmark tasks and evaluation criteria.
  • Build reliable infrastructure to run models and agents against evaluation tasks at scale.
  • Develop metrics and analyses to assess benchmark difficulty, reliability, and failure modes.
  • Validate how benchmark results relate to real-world evaluations and technical user needs.
  • Write clear technical documentation and reports that communicate findings to research and engineering audiences. WHAT WE'RE LOOKING FOR
  • Two or more years of experience in research engineering or machine learning engineering, with a focus on AI benchmarks, evaluation infrastructure, or agent environments.
  • Experience designing, implementing, and operating benchmarks or evaluation environments for AI agents or large language models.
  • Proficiency in Python, Docker, and Linux environments.
  • Experience building infrastructure to run AI models or agents reliably, and collaborating with subject-matter experts to define tasks and criteria.
  • Experience analyzing workflows across technical or business domains, and developing metrics or validation studies for benchmark quality.
  • Strong technical writing, attention to detail, and ability to work independently in unstructured environments.
  • Experience with reinforcement learning pipelines, data generation, published work, or public benchmarks is beneficial. COMPENSATION & BENEFITS Annual salary range: $100,000 to $170,000 USD. Visa sponsorship is available. LOCATION On-site in Singapore, Singapore.

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