21 hours ago
Singapore, SingaporeMid Level
Base Salary
$100k - $170k/yr
Responsibilities
- Build pipelines that transform domain-specific workflows into structured synthetic training tasks.
- Collaborate with subject-matter experts to create tasks across professional and technical domains.
- Develop methods for generating diverse, realistic, and learnable tasks.
- Create tooling to mutate, validate, and improve synthetic tasks.
- Analyze model and agent performance to identify task strengths and failure areas.
- Develop metrics for task diversity, realism, learnability, and quality.
Requirements
- At least 2 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 background with hands-on experience developing end-to-end synthetic data pipelines for AI or machine learning applications.
- Proficiency in Python, Linux development, and containerization tools such as Docker.
- Experience evaluating synthetic data quality, including diversity, realism, learnability, and limitations.
- Experience building evaluation frameworks, benchmarks, or testing environments for AI agents or large language models.
- Ability to independently deliver technical projects with minimal predefined requirements and identify subtle data inconsistencies and edge cases.
- Strong reasoning about task design, scoring, and failure modes; familiarity with reinforcement learning, agent workflows, or LLM post-training is useful.
- Clear communication skills for collaboration across time zones.
Benefits
- Base salary of $100,000 to $170,000 USD annually.
- Visa sponsorship is available.
- On-site work in Singapore, Singapore.