Alignerr · 13 hours ago
Applied Formal Methods Researcher (Lean 4)
United States
Contract
Remote
Senior Level
$70/hr - $150/hrAlignerr partners with leading AI research teams to build and train cutting-edge AI models. They are seeking an Applied Formal Methods Researcher to write and formalize advanced mathematical proofs in Lean, focusing on formal verification and translating human-written arguments into machine-verifiable formalizations.
Computer Software
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
Formalize classical proofs and compare machine-verifiable structures against textbook arguments
Investigate where automated provers break down, and articulate why (complexity, missing lemmas, insufficient libraries, etc.)
Create Lean proofs that reveal deeper patterns or generalizations implicit in the original mathematics
Qualification
Required
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
Benefits
Competitive pay and flexible remote work.
Freelance perks: autonomy, flexibility, and global collaboration.
Potential for contract extension.
Company
Alignerr
We're looking for experts to help train better AI.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase