Applied Formal Methods Researcher; Lean

Applied Formal Methods Researcher (Lean
4)

Join to apply for the Applied Formal Methods Researcher (Lean
4) role at Alignerr
.

Base pay range: $70‑$150 per hour.

Location:

Remote.

Position type:
Hourly Contract, 10‑40 hours/week.

We are seeking mathematicians with deep training in rigorous proof construction and hands‑on experience with formal proof languages, especially Lean. This role sits at the intersection of mathematics and computer science, focusing on translating human‑written mathematical arguments into precise, machine‑verifiable formalizations.

• 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, especially where tools struggle or fail.
• 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.
• Provide guidance on proof decomposition, lemma selection, and structuring techniques for formal models.
• Sample work: formalize classical proofs, investigate automation failures, create Lean proofs that reveal deeper patterns.

• 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 mathematics.
• Hands‑on experience with Lean (Lean 3 or Lean
  4), Coq, Isabelle/HOL, Agda, or comparable systems, with 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 and flexible remote work.
• Collaborate with a team working on cutting‑edge AI projects.
• Exposure to advanced LLMs and how they’re trained.
• Freelance perks: autonomy, flexibility, and global collaboration.
• Potential for contract extension.

Submit your resume, complete a short screening, and participate in project matching and onboarding.