Research Engineer, QC Automation

CLERA; Singapore; On-site; SGD 128,000 - 218,000; Full time

Job summary

Clera Labs, Inc. in Singapore seeks a Research Engineer to build automated quality control for RL training data. You will help ensure agent evaluations yield reliable, useful results by developing auditing pipelines and data validation tools.

You will collaborate across time zones, design experiments, and work with vendors to reduce anomalies in data generation while raising the bar for data quality and reproducibility.

Qualifications

• 2–4 years in QA automation or research engineering.
• Proficiency in Python, Docker and Linux.
• Experience building scalable data validation pipelines.

Responsibilities

• Automate quality control for training data in RL environments.
• Set and enforce data quality standards with evidence-based methods.
• Design experiments and metrics to evaluate agent outputs.
• Work with data vendors to investigate quality issues and improve data generation processes.
• Turn quality findings into auditing systems and validation pipelines.
• Improve infrastructure tools and vendor portals to reduce data anomalies and edge cases.

Skills

Python

Docker

Linux

QA/QC pipelines

Statistics

Communication skills

Time zone collaboration

Education

Technical education

Job 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.