Research Engineer, Synthetic Data

11 hours ago

Singapore, SingaporeMid Level / Senior

H1B sponsor

Base Salary

$150k - $250k/yr

Responsibilities

Design and build end-to-end synthetic data pipelines for scalable AI-agent training tasks.
Collaborate with subject-matter experts to create synthetic tasks across professional and technical domains.
Develop methods and tooling to generate, mutate, validate, and improve synthetic tasks at scale.
Analyze model and agent performance to identify what synthetic tasks teach and where they fail.
Define metrics for synthetic task diversity, realism, learnability, and overall quality.
Design and maintain evaluation frameworks, benchmarks, and testing environments for AI agents and large language models.
Own and deliver technical projects independently with minimal predefined requirements or roadmap.

2–4 years of experience in software engineering, machine learning engineering, or AI research, focused on data pipelines, ML infrastructure, or synthetic data systems.
Proficiency in Python and hands-on experience in Linux environments using Docker or similar containerization tools.
Demonstrated experience applying synthetic data research methods to build end-to-end data generation pipelines for AI or ML applications.
Strong understanding of synthetic data quality criteria, evaluation metrics, and their limitations.
Experience designing, implementing, or maintaining evaluation frameworks, benchmarks, or testing environments for AI agents or large language models.
Ability to reason from first principles about task design, scoring, and failure modes.
Strong attention to edge cases, inconsistencies, and quality issues in synthetic or algorithmically generated datasets.
Familiarity with reinforcement learning training paradigms, agentic AI workflows, or LLM post-training pipelines is a plus.
Strong communication skills for remote collaboration across time zones.