# Research Engineer, Benchmarks at Clera

Research Engineer, Benchmarks at Clera in Singapore. On-site, full-time, paying $100k–$170k. Posted November 5, 2026.

- Company: Clera
- Location: Singapore
- Workplace: On-site
- Job type: Full-time
- Pay: $100k–$170k
- Posted: 2026-11-05
- Apply: https://jobs.ashbyhq.com/clera/58f6f9be-99f0-469d-9334-088f40836f9e/application
- Source: https://jobmagic.ai/jobs/research-engineer-benchmarks-clera-zjw554

## 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 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.

## Description

### 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.