Clera
Research Scientist / Research Engineer
About this role
A Y Combinator-backed AI startup is hiring Research Scientists and Research Engineers to build verifier-grounded training data that improves model capabilities. You'll design scalable data generation pipelines using formal verification, physics simulators, and scientific systems while conducting original research on data quality for LLMs, robotics, and AI for science.
What you'll do
- Design and build pipelines for generating verifier-grounded training data at scale using physics simulators, formal proof systems, and scientific databases
- Develop methods to embed fundamental physics, biological facts, and logical consistency into natural language training data
- Conduct original research to advance data quality and generation techniques for large language models, robotics, and scientific AI
- Collaborate with frontier AI labs to understand data requirements and translate them into production solutions
- Prototype novel approaches, publish findings, and iterate rapidly in a high-ownership early-stage environment
What they're looking for
- Machine learning and deep learning
- LLM or generative model experience
- Python and modern ML frameworks (PyTorch, JAX)
- Data pipeline design and scalability
- Formal verification or symbolic reasoning systems
- Physics simulation environments
- Software engineering fundamentals
- Scientific research and publication
Benefits
- Competitive salary from $100,000 to $300,000 based on experience and level
- Early-stage equity
- Benefits package commensurate with well-funded startups
- Work directly with founders on high-impact research
- In-person collaboration in San Francisco
Opens the official application on the employer’s site. No login required.
Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Walk us through a research project or system you built where you had to balance theoretical rigor with practical scalability—how did you approach it?
- How would you design a data generation pipeline that ensures training data satisfies formal constraints rather than relying on human annotation?