{"schemaVersion":"jobsearcher.job.v1","id":"ca8d8df4853840bfd2100d90","url":"https://jobsearcher.com/jobs/ca8d8df4853840bfd2100d90","canonicalUrl":"https://jobsearcher.com/jobs/ca8d8df4853840bfd2100d90","title":"Lean 4 Proof Engineer - Mathematical Formalization","description":"Lean 4 Proof Engineer — Mathematical Formalization (AI Training)About The RoleWhat if your mathematical training could directly shape how AI reasons, proves, and understands the deepest structures of mathematics? We're looking for Lean 4 Proof Engineers to formalize advanced mathematical arguments for cutting-edge AI research — working at the frontier of what proof assistants can express, verify, and automate.This is a fully remote, flexible contract role built for mathematicians who think in rigorous proof and feel at home inside a formal system. If you find genuine satisfaction in taking a dense, elegant argument and expressing it in a form a machine can verify — this role was made for you.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoTranslate informal mathematical proofs into precise, machine-verifiable Lean 4 formalizations, with an emphasis on clarity, structure, and correctnessAnalyze generic and domain-specific proofs to identify gaps, hidden assumptions, and formalizable sub-structuresConstruct formalizations that test the limits of existing proof assistants — especially where automated tools struggle or fail entirelyCollaborate with AI researchers to design, refine, and evaluate strategies for improving formal verification pipelinesDevelop readable, reproducible proof scripts aligned with mathematical best practices and Lean idiomsProvide expert guidance on proof decomposition, lemma selection, and structuring techniques for formal modelsInvestigate where automated provers break down and articulate why — complexity, missing lemmas, insufficient libraries, and beyondReveal deeper patterns or generalizations implicit in the original mathematics through your formalizationsWho You AreHold a Master's degree or higher in Mathematics, Logic, Theoretical Computer Science, or a closely related fieldPossess a strong foundation in rigorous proof writing across areas such as algebra, analysis, topology, logic, or discrete mathematicsHave hands-on experience with Lean (Lean 3 or Lean 4), Coq, Isabelle/HOL, Agda, or comparable formal systems — Lean strongly preferredDeeply enthusiastic about formal verification, proof assistants, and the future of mechanized mathematicsAble to translate informal, human-written arguments into clean, structured, machine-verifiable proofsA mathematically mature problem-solver who finds the frontier of formal verification genuinely excitingNice to HaveFamiliarity with type theory, the Curry-Howard correspondence, and proof automation toolsExperience contributing to large-scale formalization projects such as MathlibExposure to theorem provers where automated reasoning frequently fails or requires manual scaffoldingPrior experience with data annotation, data quality evaluation, or AI training workflowsStrong communication skills for articulating formalization decisions, edge cases, and reasoning strategies to research collaboratorsWhy Join UsWork directly on cutting-edge AI projects alongside world-leading research labsFully remote and flexible — structure your hours around your life, not the other way aroundFreelance autonomy: choose your own pace, work asynchronously, and collaborate globallyContribute to work that sits at the genuine intersection of mathematics and AI — helping machines understand human reasoning at its most rigorousPotential for ongoing work and contract extension as new projects launch","company":"Alignerr","rawCompany":"alignerr","city":"Charlotte","state":"AR","isRemote":false,"isActive":false,"createdAt":"2026-04-09T08:03:42.210Z","occupations":[{"code":"15-2021.00","title":"Mathematicians","slug":"mathematicians"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Lean 4 Proof Engineer - Mathematical Formalization","description":"Lean 4 Proof Engineer — Mathematical Formalization (AI Training)About The RoleWhat if your mathematical training could directly shape how AI reasons, proves, and understands the deepest structures of mathematics? We're looking for Lean 4 Proof Engineers to formalize advanced mathematical arguments for cutting-edge AI research — working at the frontier of what proof assistants can express, verify, and automate.This is a fully remote, flexible contract role built for mathematicians who think in rigorous proof and feel at home inside a formal system. If you find genuine satisfaction in taking a dense, elegant argument and expressing it in a form a machine can verify — this role was made for you.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoTranslate informal mathematical proofs into precise, machine-verifiable Lean 4 formalizations, with an emphasis on clarity, structure, and correctnessAnalyze generic and domain-specific proofs to identify gaps, hidden assumptions, and formalizable sub-structuresConstruct formalizations that test the limits of existing proof assistants — especially where automated tools struggle or fail entirelyCollaborate with AI researchers to design, refine, and evaluate strategies for improving formal verification pipelinesDevelop readable, reproducible proof scripts aligned with mathematical best practices and Lean idiomsProvide expert guidance on proof decomposition, lemma selection, and structuring techniques for formal modelsInvestigate where automated provers break down and articulate why — complexity, missing lemmas, insufficient libraries, and beyondReveal deeper patterns or generalizations implicit in the original mathematics through your formalizationsWho You AreHold a Master's degree or higher in Mathematics, Logic, Theoretical Computer Science, or a closely related fieldPossess a strong foundation in rigorous proof writing across areas such as algebra, analysis, topology, logic, or discrete mathematicsHave hands-on experience with Lean (Lean 3 or Lean 4), Coq, Isabelle/HOL, Agda, or comparable formal systems — Lean strongly preferredDeeply enthusiastic about formal verification, proof assistants, and the future of mechanized mathematicsAble to translate informal, human-written arguments into clean, structured, machine-verifiable proofsA mathematically mature problem-solver who finds the frontier of formal verification genuinely excitingNice to HaveFamiliarity with type theory, the Curry-Howard correspondence, and proof automation toolsExperience contributing to large-scale formalization projects such as MathlibExposure to theorem provers where automated reasoning frequently fails or requires manual scaffoldingPrior experience with data annotation, data quality evaluation, or AI training workflowsStrong communication skills for articulating formalization decisions, edge cases, and reasoning strategies to research collaboratorsWhy Join UsWork directly on cutting-edge AI projects alongside world-leading research labsFully remote and flexible — structure your hours around your life, not the other way aroundFreelance autonomy: choose your own pace, work asynchronously, and collaborate globallyContribute to work that sits at the genuine intersection of mathematics and AI — helping machines understand human reasoning at its most rigorousPotential for ongoing work and contract extension as new projects launch","datePosted":"2026-04-09T08:03:42.210Z","dateModified":"2026-04-09T08:03:42.210Z","hiringOrganization":{"@type":"Organization","name":"Alignerr","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Charlotte","addressRegion":"AR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ca8d8df4853840bfd2100d90"},"url":"https://jobsearcher.com/jobs/ca8d8df4853840bfd2100d90"}}