Research Engineer, Synthetic Data (Pacific Time)

Role overview Build a synthetic data pipeline that turns professional and technical workflows into useful training tasks for AI agents. This hands-on research engineering role spans task design, generation systems, evaluation, and analysis of what models learn; it includes taking early research through to dependable pipelines in areas where the path is not fully defined.

Responsibilities - Work with subject-matter experts to develop training tasks across professional and technical domains. - Design generation approaches that produce varied, realistic, and learnable tasks. - Build tools to mutate, validate, and improve generated tasks. - Evaluate model and agent results to identify what tasks teach and where performance breaks down. - Create measures for task diversity, realism, learnability, and related qualities. - Develop pipeline methods and systems from initial research into reliable operation.

Requirements - Proficiency with Python, Docker, and Linux. - Experience with synthetic data research methods and an understanding of the quality and limitations of synthetic data. - Experience building synthetic data pipelines end to end, including work without a prescribed roadmap. - Experience with environments, evaluations, or benchmarks. - Clear written and spoken English and ability to collaborate across time zones.

Nice to have - Careful attention to subtle inconsistencies and edge cases in generated data. - First-principles reasoning about task design, scoring, and failure modes. - Comfort working in early-stage or otherwise unstructured settings.

Benefits and work setup - Full-time role, with on-site options in San Francisco or Singapore, or remote work from Singapore or US Pacific time zones. Remote schedules should overlap roughly 70–80% with business hours in one of those regions; exact hours are agreed during hiring. - Technical aptitude and learning potential are emphasized over years of experience, and applicants need not meet every listed qualification.