Lean Proof Engineer - Mathematical Formalization

Overview

At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models. Write and formalize advanced mathematical proofs in Lean for cutting-edge AI research. Ideal for mathematicians passionate about formal verification and pushing the limits of modern proof assistants.

• Translate informal mathematical proofs into Lean (and related proof systems) 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.
• Formalize classical proofs and compare machine-verifiable structures against textbook arguments; investigate where automated provers break down and articulate why.

• 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, 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.

• A mathematically mature problem-solver who enjoys working at the frontier of formal verification; someone who finds satisfaction in taking a dense, elegant human argument and expressing it in a form that a machine can understand.

• 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
• Project matching and onboarding