Research Engineer, Synthetic Data
At a glance
Mid-level AI Research role at Clera. Singapore · full-time · $100,000–$170,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Convert specialized work processes into realistic, structured training exercises for AI systems
- Shape exercises with subject experts across technical and professional fields
- Build approaches and tooling to generate, vary, check and improve synthetic tasks
- Review model and agent results, identify failure patterns, and assess task quality and diversity
What you bring
- At least two years in a technical role spanning software, machine learning engineering or AI research
- You have applied synthetic data techniques to create end-to-end generation pipelines for AI or machine learning
- You can use Python, Linux and containerization software such as Docker
- You have experience with AI agent or language-model evaluations, benchmarks or testing environments
Who this fits
This role suits a technical researcher or engineer who can carry projects from loosely defined problems through delivery. The position is on-site in Singapore, and visa sponsorship is available.
From the employer
About the Role
Join a research and engineering team building synthetic data systems for AI agents. You will develop methods and infrastructure that turn real-world workflows into high-quality training tasks, helping expand and evaluate model capabilities.
What You'll Do
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 understand task effectiveness and identify failure modes.
Create metrics to assess task diversity, realism, learnability, and overall quality.
What We're Looking For
Two or more 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, Linux, and 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.
Ability to own technical projects from conception through delivery in loosely defined problem spaces.
Strong attention to detail, communication skills, and ability to reason about task design, scoring, and edge cases.
Familiarity with reinforcement learning, agent workflows, or LLM post-training is helpful.
Compensation & Benefits
Annual salary range: $100,000 to $170,000 USD. Visa sponsorship is available.
Location
On-site in Singapore, Singapore.