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Research Engineer, Benchmarks

On-site
CleraSingapore, SG23 hours agoWebsite
Fresh
Full-time
Engineering

Compensation

Salary undisclosed
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Description

About the Role

Join a small, technical team working on AI evaluation and reinforcement learning infrastructure. You will design and build rigorous benchmarks for assessing AI agents on realistic, domain-specific workflows, helping research and engineering teams understand how well agents perform in practice.

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 practical tasks and evaluation criteria.

  • Build reliable infrastructure to run models and agents against benchmark tasks at scale.

  • Develop metrics and analyses to assess benchmark difficulty, reliability, and failure modes.

  • Validate benchmark results against real-world evaluations and user needs.

  • Write clear technical documentation and reports that explain methods and results.

What We're Looking For

  • Two to four years of experience in software engineering, machine learning engineering, or research, including at least two years building AI benchmarks, evaluation infrastructure, or agent environments.

  • Hands-on experience designing and running evaluations or benchmark environments for AI agents or large language models.

  • Strong proficiency with Python, Docker, and Linux, including building and operating reliable infrastructure.

  • Experience developing metrics, statistical analyses, or validation studies for evaluation systems.

  • Experience collaborating with subject-matter experts and understanding workflows across technical or business domains.

  • Strong technical writing, careful attention to detail, and the ability to work independently in an early-stage, fast-moving environment.

  • Research publications or technical writing on benchmarking, model evaluation, or failure modes are beneficial. Experience with reinforcement learning pipelines or public benchmark projects is also useful.

Compensation & Benefits

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

Location

On-site in Singapore, Singapore.

Stack

LLMsPythonAgentic AIMachine LearningDockerReinforcement Learning
Posted
Oct 20, 2026
Last seen
Oct 20, 2026
First seen
Oct 20, 2026

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