Research Engineer, Synthetic Data

About the Role

Join an engineering team at an early-stage AI company building infrastructure for training and evaluating AI agents. You will develop synthetic data methods and systems that turn real-world workflows into useful training tasks, helping expand agent capabilities across professional and technical domains.

What You'll Do

• Build pipelines that transform domain-specific workflows into realistic, structured, and challenging synthetic training tasks.
• Collaborate with subject-matter experts to create tasks across professional and technical domains.
• Design generation methods and tools to mutate, validate, and improve synthetic tasks.
• Analyze model and agent performance to understand task strengths, gaps, and failure modes.
• Develop metrics for assessing task diversity, realism, learnability, and overall quality.

What We're Looking For

• Two to four years of relevant experience, with at least two years in software engineering, machine learning engineering, or AI research roles.
• Hands-on experience building end-to-end synthetic data generation pipelines for AI or machine learning applications.
• Proficiency in Python and experience working in Linux environments with Docker or similar containerization tools.
• Practical knowledge of synthetic data quality, evaluation metrics, and the limitations of generated data.
• Experience building automated systems for generating, validating, mutating, or processing structured datasets at scale.
• Background in AI agent or language model evaluation, benchmarks, testing environments, or post-training workflows.
• Ability to independently deliver technical projects, reason carefully about edge cases, and work effectively in an unstructured environment.

Compensation & Benefits

Annual salary: USD $150,000 to $250,000. Visa sponsorship is available.

Location

On-site in Singapore, Singapore.