# Research Engineer, Synthetic Data - Company: [Clera]() - Location: San Francisco - Team: Engineering - Employment type: Full Time - Salary: $150K – $250K - Posted: August 27, 2026 ## Job description ### About the Role This is a Research Engineer role focused on building synthetic data pipelines for AI agent training, sitting within a ~15-person engineering team of Olympiad medalists and published researchers. You'll design generation methods, validation systems, and quality metrics that directly expand model capabilities — work that sits at the frontier of RL-based AI alignment. ### What You'll Do * Build end-to-end synthetic data pipelines that transform domain-specific workflows into structured, challenging training tasks for AI agents. * Collaborate with subject-matter experts to develop synthetic tasks spanning professional and technical domains. * Design task generation methods that produce diverse, realistic, and learnable training examples. * Build tooling to mutate, validate, and iteratively improve synthetic task quality. * Analyze model and agent performance on synthetic tasks to understand learning outcomes and failure modes. * Develop metrics to quantify synthetic task diversity, realism, learnability, and overall quality. ### What We're Looking For * 2–4 years of experience in software engineering, ML engineering, or AI research roles delivering data pipelines, ML infrastructure, or synthetic data systems. * Hands-on experience applying synthetic data research methods to build end-to-end data generation pipelines for AI/ML applications. * Proficiency in Python and experience developing in Linux environments using containerization tools such as Docker. * Demonstrated understanding of synthetic data quality criteria and evaluation metrics — diversity, realism, learnability — and their inherent limitations. * Experience designing, implementing, or maintaining evaluation frameworks, benchmarks, or testing environments for AI agents or large language models. * Experience building automated systems to generate, validate, mutate, or process structured datasets at scale. * Track record of independently owning and delivering technical projects end-to-end with minimal predefined requirements. * Ability to detect edge cases, inconsistencies, and quality issues in synthetic or algorithmically generated datasets. * Comfort operating in unstructured, early-stage environments and reasoning from first principles. * Strong communication skills for effective remote collaboration across time zones. * **Nice to have:** Familiarity with reinforcement learning paradigms, agentic AI workflows, or LLM post-training pipelines. ### Compensation & Benefits Salary range: **$150,000 – $250,000 USD annually.** Visa sponsorship is available. ### Location On-site in **San Francisco, CA, United States**. Singapore-based candidates are also considered. ## Apply [Apply on Clera]() Canonical job page: