6 hours ago
Singapore (city not specified)Mid Level
Base Salary
$100k - $170k/yr
Responsibilities
- Build scalable pipelines that convert professional and technical workflows into realistic, structured training tasks.
- Collaborate with subject-matter experts to develop tasks across distinct domains.
- Design methods for generating diverse, realistic, and learnable synthetic tasks.
- Create tools to mutate, validate, and improve generated tasks.
- Analyze agent performance, identify failure modes, and develop metrics for task quality.
- Build evaluation frameworks, benchmarks, or testing environments for AI agents and large language models.
Requirements
- At least two years of experience in software engineering, machine learning engineering, or AI research building and delivering data pipelines, ML infrastructure, or synthetic data systems.
- Technical education or equivalent technical background, with strong Python skills and experience in Linux environments and Docker.
- Hands-on experience applying synthetic data methods to build end-to-end generation pipelines for AI or machine learning.
- Understanding of synthetic data quality, evaluation criteria, and limitations.
- Ability to independently deliver projects in open-ended settings with careful attention to data quality and edge cases.
- Familiarity with reinforcement learning, agent workflows, or LLM post-training is valuable.
Benefits
- Visa sponsorship is available.
- The role is onsite in Singapore, Singapore.