Clera
Singapore
Synthetic Data Engineer for AI Agents
- AI
- Containerization
- Docker
- Linux
AI Summary
Own the design and implementation of rigorous, domain-specific benchmarks for frontier AI agents. Build evaluation infrastructure, metrics, analyses, and technical documentation for agent performance. Requires 2-4 years in research or ML engineering, strong Python, Docker, and Linux skills.
Key Highlights
Own design and implementation of domain-specific AI agent benchmarks
Build infrastructure to run models and agents at scale
Develop metrics, analyses, and validation studies
Collaborate with subject-matter experts across domains
On-site role in Singapore with visa sponsorship available
Key Responsibilities
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
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Technical Skills Required
Benefits & Perks
Visa sponsorship
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Nice to Have
Published research or technical writing on benchmarking, model evaluation, or failure modes
Reinforcement learning pipelines, data generation, and agent evaluation experience
Job 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
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