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EmploymentFull-time
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ABOUT THE ROLE
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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.
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