Research Engineer, Synthetic Data (Mid-Level)

ABOUT THE ROLE Join an AI evaluation and reinforcement learning team building synthetic data pipelines for AI agents. You will turn real-world professional workflows into scalable training tasks and develop ways to measure whether those tasks improve model capabilities. 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.
• Develop methods and tools to generate, mutate, validate, and improve synthetic tasks.
• Analyze agent performance to understand what tasks teach and where they fail.
• Create metrics for task diversity, realism, learnability, and overall quality. WHAT WE'RE LOOKING FOR
• Two or more years in software engineering, machine learning engineering, or AI research, with relevant experience building data pipelines or ML infrastructure.
• Hands-on experience applying synthetic data research methods to build end-to-end generation pipelines.
• Proficiency in Python and experience working in Linux environments with Docker.
• Understanding of synthetic data quality, evaluation metrics, and the limitations of generated data.
• Experience building evaluation frameworks, benchmarks, or testing environments for AI agents or language models.
• Ability to independently deliver technical projects, build automated data systems, and spot subtle quality issues and edge cases.
• Familiarity with reinforcement learning, agent workflows, or model post-training is useful. COMPENSATION & BENEFITS Salary range: USD 100,000 to 170,000 annually. Visa sponsorship is available. LOCATION On-site in Singapore, Singapore.