Research Engineer, Synthetic Data (Visa Sponsorship - Singapore, Singapore)

Visa sponsorship available. A small engineering team builds synthetic data systems used to train AI agents. The work centers on converting real professional and technical workflows into structured, scalable training tasks that help models learn and perform in practical settings. You will join a tight team and own projects from design through delivery, working in a loosely defined problem space.

What you'll do

• Build pipelines that turn domain-specific workflows into realistic, structured synthetic training tasks.
• Partner with subject-matter experts to author tasks for AI agents across professional and technical fields.
• Design generation methods that produce tasks that are diverse, realistic and learnable.
• Develop tools to mutate, validate and refine synthetic tasks.
• Analyze agent and model performance to identify task strengths, limitations and failure modes.
• Define metrics for task diversity, realism, learnability and overall quality.

What you need

• At least two years of experience in software engineering, machine learning engineering or AI research.
• Hands-on experience building end-to-end data generation pipelines for AI or machine learning, including synthetic data methods.
• Strong Python skills and experience working in Linux with containerization tools such as Docker.
• Understanding of synthetic data quality criteria, evaluation metrics and the limits of synthetic data.
• Experience building or maintaining evaluation frameworks, benchmarks or test environments for AI agents or large language models is a plus.
• Ability to deliver technical projects independently, with attention to edge cases and data quality. Familiarity with reinforcement learning, agent workflows or LLM post-training is useful.

How to apply

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