Applied Formal Methods Researcher; Lean

Applied Formal Methods Researcher (Lean
4)

We partner with leading AI research teams to build cutting‑edge models. The role sits at the intersection of mathematics and computer science, focusing on translating human‑written mathematical arguments into precise, machine‑verifiable formalizations.

We seek mathematicians with deep training in rigorous proof construction and hands‑on experience with formal proof languages, especially Lean. The role involves pushing the limits of formal verification, capturing gaps, and developing strategies for improving verification pipelines.

• Translate informal mathematical proofs into Lean with an emphasis on clarity, structure, and correctness.
• Analyze generic and domain‑specific proofs, identifying gaps, hidden assumptions, and formalizable sub‑structures.
• Construct formalizations that test the limits of existing proof assistants; many tools struggle or fail—help map the frontier.
• Collaborate with researchers to design, refine, and evaluate strategies for improving formal verification pipelines.
• Develop highly readable, reproducible proof scripts aligned with mathematical best practices and proof assistant idioms.
• Guide proof decomposition, lemma selection, and structuring techniques for formal models.

• Master’s degree (or higher) in Mathematics, Logic, Theoretical Computer Science, or a closely related field.
• Strong foundation in rigorous proof writing and mathematical reasoning across areas such as algebra, analysis, topology, logic, or discrete math.
• Hands‑on experience with Lean (Lean 3 or Lean
  4), Coq, Isabelle/HOL, Agda, or comparable systems;
  Lean strongly preferred.
• Deep enthusiasm for formal verification, proof assistants, and the future of mechanized mathematics.
• Ability to translate informal arguments into clean, structured formal proofs.

• Prior experience with data annotation, data quality, or evaluation systems.
• Familiarity with type theory, Curry‑Howard correspondence, and proof automation tools.
• Experience with large‑scale formalization projects (e.g., mathlib).
• Exposure to theorem provers where automated reasoning frequently fails or requires manual scaffolding.
• Strong communication skills for explaining formalization decisions, edge cases, and reasoning strategies.

• Competitive pay ($70–$150 /hour).
• Remote work; flexible hours 10–40 hrs/week.
• Collaborate with AI projects; exposure to advanced LLMs and how they’re trained.
• Freelance perks: autonomy, flexibility, global collaboration.
• Potential contract extension.

$70–$150 /hour

Remote

10–40 hours/week