# Research Engineer, QC Automation at Clera

Research Engineer, QC Automation at Clera in Singapore. On-site, full-time, paying $100k–$170k. Posted October 28, 2026.

- Company: Clera
- Location: Singapore
- Workplace: On-site
- Job type: Full-time
- Pay: $100k–$170k
- Posted: 2026-10-28
- Apply: https://jobs.ashbyhq.com/clera/36e2e311-5023-4fb3-8bc0-4015d2a3124c/application
- Source: https://jobmagic.ai/jobs/research-engineer-qc-automation-clera-khkx0d

## Requirements

- Two to four years of experience in a research engineering or similar role focused on quality-control automation, plus a degree in a technical field.
- Proficiency with Python, Docker, and Linux.
- Experience independently building scalable data-validation pipelines and end-to-end automated QA or QC systems.
- Background in benchmarks and evaluations for reinforcement learning data, including realistic task design, reliable rubrics, and useful training trajectories.
- Experience defining and measuring training-data quality, and designing experiments, metrics, and quality processes.
- Strong statistical knowledge and the ability to communicate clearly across time zones and work independently in an unstructured startup environment.

## Description

### About the Role

Join an engineering team at an early-stage AI infrastructure company focused on reinforcement learning environments and evaluation. You will build quality-control systems for training data, helping ensure that data and evaluations are reliable as demand grows.

### What You'll Do

- Automate quality control for training data produced using the company's infrastructure.

- Define and enforce clear quality standards using human judgment and careful analysis, rather than relying heavily on large language models.

- Design experiments and metrics to assess agent outputs and evaluation quality.

- Work with data vendors to investigate quality issues, diagnose agent failure modes, and improve data-generation processes.

- Turn quality-control findings into auditing systems, sampling strategies, and rule-based or model-assisted validation pipelines.

- Improve infrastructure tools and vendor-facing workflows to reduce anomalies, inconsistencies, and edge cases.

### What We're Looking For

- Two to four years of experience in a research engineering or similar role focused on quality-control automation, plus a degree in a technical field.

- Proficiency with Python, Docker, and Linux.

- Experience independently building scalable data-validation pipelines and end-to-end automated QA or QC systems.

- Background in benchmarks and evaluations for reinforcement learning data, including realistic task design, reliable rubrics, and useful training trajectories.

- Experience defining and measuring training-data quality, and designing experiments, metrics, and quality processes.

- Strong statistical knowledge and the ability to communicate clearly across time zones and work independently in an unstructured startup environment.

### Compensation & Benefits

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

### Location

On-site in Singapore, Singapore.