# Research Engineer, QC Automation at Clera

Research Engineer, QC Automation 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/dbc6684e-3338-46d1-8711-efc6999c26aa/application
- Source: https://jobmagic.ai/jobs/research-engineer-qc-automation-clera-daxjmn

## Requirements

- Two to four years of experience as a research engineer or in a similar engineering or research role focused on quality control automation.
- Technical education or equivalent technical experience, with proficiency in Python, Docker, and Linux.
- Experience building scalable data validation pipelines and end-to-end automated QA/QC systems with autonomy in unstructured problem spaces.
- Background in benchmarks and evaluations for reinforcement learning training data, including defining realistic tasks, reliable rubrics, and useful trajectories.
- Experience defining and measuring training data quality, and designing evaluation metrics, experiments, and QA/QC processes.
- Knowledge of statistics, strong communication skills, curiosity across domains, and the ability to collaborate independently across time zones.

## Description

### About the Role

Join a small engineering team at an AI and reinforcement learning infrastructure company. You will build quality control systems for training data and help ensure that agent evaluations produce reliable, useful results.

### What You'll Do

- Automate quality control for training data generated in reinforcement learning environments.

- Set and enforce data quality standards using human judgment and clear evidence rather than relying heavily on large language models.

- Design experiments and metrics to evaluate agent outputs.

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

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

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

### What We're Looking For

- Two to four years of experience as a research engineer or in a similar engineering or research role focused on quality control automation.

- Technical education or equivalent technical experience, with proficiency in Python, Docker, and Linux.

- Experience building scalable data validation pipelines and end-to-end automated QA/QC systems with autonomy in unstructured problem spaces.

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

- Experience defining and measuring training data quality, and designing evaluation metrics, experiments, and QA/QC processes.

- Knowledge of statistics, strong communication skills, curiosity across domains, and the ability to collaborate independently across time zones.

### Compensation & Benefits

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

### Location

On-site in Singapore, Singapore.