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    Research Engineer, Benchmarks

    CleraOn-site - Singapore, SingaporePosted 2026-11-05
    This listing's locations
    On-site - Singapore, Singapore
    Employment
    Full-time
    Workplace
    On site
    Compensation
    100000 (period not stated)
    Department: Engineering

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    About the Role

    Join a small, technical team at an early-stage AI evaluation company building benchmarks for frontier AI agents. You will own the design and implementation of rigorous, domain-specific evaluations that help research teams and customers understand real-world agent performance.

    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 realistic tasks and evaluation criteria.
    • Build reliable infrastructure for running models and agents against benchmark 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 user needs.
    • Write clear technical documentation and reports communicating benchmark methods and results.

    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 or delivering AI benchmarks, evaluation infrastructure, or agent environments.
    • Strong proficiency in Python, Docker, and Linux for research or production infrastructure.
    • Hands-on experience designing, implementing, and operating evaluations for AI agents or large language models.
    • Experience building infrastructure to run models or agents reliably, and developing metrics, statistical analyses, or validation studies.
    • Ability to collaborate with subject-matter experts and analyze workflows across different domains to create useful evaluation tasks.
    • Strong technical writing, attention to detail, first-principles reasoning, and comfort working independently in a fast-paced startup.
    • Published research or technical writing on benchmarking, model evaluation, or failure modes is valued. Reinforcement learning pipelines, data generation, and agent evaluation experience are also relevant.

    Compensation & Benefits

    Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.

    Location

    On-site in Singapore, Singapore.

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