Research Scientist / Research Engineer

ABOUT THE ROLE

We are an early-stage, Y Combinator-backed startup at the frontier of AI training data — building the next generation of verifier-grounded, correct-by-construction training data for advanced AI systems. Our work spans large language models (LLMs), robotics, and AI for science. We believe that breakthroughs in model capability are fundamentally gated on breakthroughs in data quality, and we're building the infrastructure to make that possible.

We are hiring both Research Scientists and Research Engineers to join our founding team. You'll work directly with the founders and have an outsized impact on the technical direction of the company from day one.

WHAT YOU'LL DO

• Design and develop methods for generating high-quality, verifiable training data grounded in formal systems — including physics simulators, scientific databases, formal proof systems, and executable tests.

• Research and implement techniques that project fundamental laws of physics, biological facts, and self-consistent logic into natural language data.

• Build scalable pipelines and tooling for data generation, validation, and quality assurance.

• Collaborate closely on research agendas targeting frontier AI models in LLMs, robotics, and scientific AI.

• Contribute to publications, benchmarks, and other artifacts that advance the field of AI training data.

WHAT WE'RE LOOKING FOR

We are open to a range of backgrounds and experience levels (0–12 years). We value strong fundamentals, intellectual curiosity, and a bias toward execution. Relevant backgrounds include:

• Research Scientists: Deep expertise in machine learning, deep learning, NLP, robotics, or AI for science. Track record of publishing or producing impactful research.

• Research Engineers: Strong software engineering skills with experience building ML systems, data pipelines, or research infrastructure at scale.

• Experience with formal methods, theorem proving, symbolic AI, physics simulation, or scientific computing is a strong plus.

• Familiarity with LLM training, fine-tuning, or RLHF pipelines is highly desirable.

• Background from companies or research groups working on robotics, AI training data, or frontier model development is a plus.

• Ability and willingness to work on-site in San Francisco.

Note: Visa sponsorship is not available for this role. Candidates must be authorized to work in the United States.

COMPENSATION & BENEFITS

• Salary: $100,000 – $300,000 USD annually, depending on role level and experience.

• Equity in an early-stage, high-growth company backed by a top-tier accelerator.

• Opportunity to shape the technical and research culture of the company from the ground up.

LOCATION

• San Francisco, CA, USA — on-site.

• Candidates must be based in San Francisco or willing to relocate.