Research Engineer, Synthetic Data

About the role

A fast-growing AI company building infrastructure for AI training data is looking for a Research Engineer, Synthetic Data. The company's marketplace connects data creators with AI labs, and is used by startups, large companies and frontier labs. The role builds the synthetic data pipeline: turning domain-specific workflows into synthetic training tasks that are realistic, structured and challenging enough to expand model capabilities. It is a hands-on research engineering seat, not a commercial or privacy-systems role.

The position is full-time, starting ASAP, and is available on-site in San Francisco or Singapore, or remotely within the Singapore or US Pacific time zones, with about 70-80% overlap with the respective business hours. The exact daily schedule is agreed during hiring.

Key responsibilities

• Work with subject-matter experts to create synthetic tasks for training AI agents across professional and technical domains.
• Design synthetic task-generation methods that produce diverse, realistic and learnable tasks.
• Build systems and tooling to mutate, validate and improve synthetic tasks.
• Analyse model and agent performance on synthetic tasks to understand what they teach and where they fail.
• Develop metrics for synthetic task diversity, realism and learnability.
• Take synthetic data pipelines from early research through to reliable systems, including where the roadmap is not fully prescribed.

Required profile

• Experience with synthetic data research methods, ready to describe them in the application.
• Strong understanding of what good synthetic data means and its limitations.
• Experience building synthetic data pipelines end to end, including where there was no fully prescribed roadmap.
• Experience working on environments, evals or benchmarks.
• Clear written and spoken English and comfort collaborating remotely across time zones.
• Technical aptitude and learning potential matter more than years of experience; motivated candidates are encouraged to apply even if they do not meet every point.

Required skills

• Proficiency in Python, Docker and Linux environments.
• Ability to reason from first principles about task design, scoring and failure modes.