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Research Engineer - Quality Control for RL Training Data

clera • Singapore
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AI Summary

Join a small engineering team at an AI and reinforcement learning infrastructure company to build quality control systems for training data. You will automate QC for RL training data, design evaluation metrics and experiments, and work with data vendors to diagnose failure modes. Requires 2-4 years of experience, proficiency in Python, Docker, and Linux, and background in RL benchmarks and evaluations.

Key Highlights
Build quality control systems for RL training data
Design experiments and metrics to evaluate agent outputs
Work with data vendors to diagnose failure modes
2-4 years experience; Python, Docker, Linux required
On-site in Singapore; visa sponsorship available

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Key Responsibilities
Automate quality control for training data generated in reinforcement learning environments
Set and enforce data quality standards using human judgment and clear evidence
Design experiments and metrics to evaluate agent outputs
Work with data vendors to investigate quality issues and diagnose agent failure modes
Turn quality findings into auditing systems including sampling strategies and validation pipelines
Improve infrastructure tools and vendor portals to reduce anomalies and edge cases
Technical Skills Required
Python Docker Linux

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Benefits & Perks
Visa sponsorship available

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

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Job Overview
Posted Nov 06, 2026
Employment Full-time
Experience Mid-Senior level
Location Singapore
Category Programming
Company clera
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