Overview
Location: Remote. Alignerr partners 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.
Responsibilities
* 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.
* Sample Work You Might Do:
o Formalize classical proofs and compare machine-verifiable structures against textbook arguments.
o Investigate where automated provers break down, and articulate why (complexity, missing lemmas, insufficient libraries, etc.).
o Create Lean proofs that reveal deeper patterns or generalizations implicit in the original mathematics.
Qualifications
* 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.
Preferred
* 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.
* Ideal Candidate — a mathematically mature problem-solver who enjoys working at the frontier of formal verification and values precision and structure.
Why Join Us
* 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.
Application Process
* Submit your resume.
* Complete a short screening.
* Project matching and onboarding.
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
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