Research Engineer, Synthetic Data
Clera Singapore, Singapore · $100K–$170K/yr
Technology, Information and Internet · 11-50 employees
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About the role
You will build and maintain pipelines to transform professional workflows into structured synthetic training tasks for AI agents. Additionally, you will develop tools to validate these datasets and analyze model performance to improve task quality and learnability.
What they look for
Requirements
Candidates must have at least two years of experience in software or machine learning engineering with proficiency in Python and Linux. Experience with synthetic data generation, containerization tools like Docker, and evaluation frameworks for AI models is required.
Benefits
Full description
About the Role
Join a small engineering team building synthetic data systems for AI agents. You will turn real-world professional workflows into scalable training tasks, helping improve how models learn and perform across practical domains.
What You'll Do
- Build pipelines that transform domain-specific workflows into realistic, structured synthetic training tasks.
- Work with subject-matter experts to create tasks for AI agents across professional and technical domains.
- Design generation methods that produce diverse, realistic, and learnable tasks.
- Develop tools to mutate, validate, and improve synthetic tasks.
- Analyze model and agent performance to understand task strengths, limitations, and failure modes.
- Create metrics for task diversity, realism, learnability, and overall quality.
What We're Looking For
- Two or more years of relevant experience in software engineering, machine learning engineering, or AI research, with a technical background.
- Hands-on experience applying synthetic data methods and delivering end-to-end data generation pipelines for AI or machine learning applications.
- Proficiency in Python and experience working in Linux environments with containerization tools such as Docker.
- Experience with synthetic data quality criteria, evaluation metrics, and the limitations of synthetic data.
- Background building or maintaining evaluation frameworks, benchmarks, or testing environments for AI agents or large language models.
- Experience automating the generation, validation, mutation, or processing of structured datasets at scale.
- Ability to independently deliver technical projects in loosely defined problem spaces, with care for edge cases and data quality.
- Familiarity with reinforcement learning, agent workflows, or LLM post-training is useful.
Compensation & Benefits
Base salary range: $100,000 to $170,000 USD annually. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.
