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Research Engineer, Benchmarks

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Research Engineer, Benchmarks in Others

  • Singapore, Singapore

Responsibilities

  • Design, implement, and own internal benchmarks for evaluating frontier agents on domain-specific tasks.
  • Partner with subject-matter experts to define realistic workflows and evaluation criteria.
  • Build scalable infrastructure to run models and agents against benchmark tasks using Python, Docker, and Linux.
  • Develop metrics and statistical analyses for benchmark difficulty, reliability, and failure modes.
  • Validate benchmark performance against real-world evaluations and customer needs.
  • Write technical documentation and benchmark reports for research and engineering audiences.

Requirements

  • 2 to 4 years of experience in research engineering or machine learning engineering, focused on AI benchmarks, evaluation infrastructure, or agent environments.
  • Strong proficiency in Python, Docker, and Linux.
  • Experience designing and running benchmarks or evaluation environments for AI agents or large language models.
  • Experience developing metrics, statistical analyses, or validation studies for benchmark quality and real-world correlation.
  • Experience translating workflows into structured evaluation tasks with domain experts.
  • Strong technical writing skills; published papers or technical posts on AI benchmarking, model evaluation, or failure modes are a plus.
  • Ability to reason from first principles about task design, scoring, and edge cases.
  • Ability to work independently in fast-paced, early-stage startup environments.
  • Experience with reinforcement learning training pipelines, data generation, or RL agent evaluation is a bonus.

Benefits

  • Salary range of $150,000 to $250,000 USD annually.
  • Visa sponsorship is available.
  • Full-time, in-person role on-site in Singapore.

Salary: $150k - $250k/yr

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