3 days ago
Singapore, SingaporeMid Level / Senior
Base Salary
$100k - $170k/yr
Responsibilities
- Design, implement, and maintain benchmarks for evaluating AI agents on domain-specific tasks.
- Collaborate 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 for benchmark difficulty, reliability, and failure modes.
- Validate benchmark results against real-world evaluations and user needs.
- Write technical documentation and reports communicating benchmark methods and results.
Requirements
- 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 reliable model or agent infrastructure and developing metrics, statistical analyses, or validation studies.
- Ability to collaborate with subject-matter experts and analyze workflows across domains.
- Strong technical writing, attention to detail, first-principles reasoning, and ability to work 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.
Benefits
- Base salary of $100,000 to $170,000 USD annually.
- Visa sponsorship is available.
- On-site work in Singapore, Singapore.