1 day ago
Singapore, SingaporeMid Level
Base Salary
$100k - $170k/yr
Responsibilities
- 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 methods for generating diverse, realistic, and learnable tasks.
- Develop tools to mutate, validate, and improve synthetic tasks.
- Analyze model and agent performance to assess task effectiveness and identify failure modes.
- Create metrics for task diversity, realism, learnability, and overall quality.
- Own technical projects from conception through delivery in loosely defined problem spaces.
Requirements
- At least two years of experience in software engineering, machine learning engineering, or AI research with a technical background.
- Hands-on experience applying synthetic data methods to build end-to-end data-generation pipelines for AI or machine learning.
- Proficiency in Python and Linux, plus containerization tools such as Docker.
- Experience with evaluation frameworks, benchmarks, or testing environments for AI agents or large language models.
- Understanding of synthetic data quality, evaluation metrics, and limitations backed by research or production work.
- Experience building automated systems to generate, validate, mutate, or process structured data at scale.
- Strong attention to detail, communication, and reasoning about task design, scoring, and edge cases.
- Familiarity with reinforcement learning, agent workflows, or LLM post-training is helpful.
Benefits
- Annual salary range of $100,000 to $170,000 USD.
- Visa sponsorship is available.
- On-site work in Singapore, Singapore.