4 days ago
Singapore, SingaporeMid Level
Base Salary
$100k - $170k/yr
Responsibilities
- Build scalable pipelines that transform professional workflows into structured synthetic training tasks.
- Collaborate with subject-matter experts to create tasks for AI agents across professional and technical domains.
- Design methods for generating diverse, realistic, and learnable tasks.
- Develop tools to mutate, validate, improve, and process synthetic tasks and structured datasets at scale.
- Analyze model and agent performance, including strengths, limitations, and failure modes.
- Create metrics and evaluation frameworks for task diversity, realism, learnability, and overall quality.
Requirements
- At least two 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 synthetic data limitations.
- Experience 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 attention to edge cases and data quality.
- Familiarity with reinforcement learning, agent workflows, or LLM post-training is useful.
Benefits
- Base salary range of $100,000 to $170,000 USD annually.
- Visa sponsorship is available.
- On-site work in Singapore, Singapore.