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Formal Verification Scientist; Lean 4 & Mathlib

Job in Jacksonville, Duval County, Florida, 32290, USA
Listing for: Alignerr Corp.
Full Time position
Listed on 2026-10-11
Job specializations:
  • IT/Tech
    Mathematics, AI Business & Operations, AI Evaluation, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 83000 - 165000 USD Yearly USD 83000.00 165000.00 YEAR
Job Description & How to Apply Below
Position: Formal Verification Scientist (Lean 4 & Mathlib)
About

The Role

What if your deep mathematical expertise could directly shape how the world's most advanced AI systems understand and reason about formal proof? We're looking for Formal Verification Scientists to translate rigorous human-written mathematics into machine-verifiable Lean 4 proofs — working at the very frontier of what proof assistants can express, capture, and automate.

About

The Role

What if your deep mathematical expertise could directly shape how the world's most advanced AI systems understand and reason about formal proof? We're looking for Formal Verification Scientists to translate rigorous human-written mathematics into machine-verifiable Lean 4 proofs — working at the very frontier of what proof assistants can express, capture, and automate.

This is a fully remote, flexible contract role designed for mathematicians who live and breathe formal reasoning. If you find satisfaction in taking a dense, elegant argument and expressing it in a form a machine can verify — this role was made for you.

  • Organization:
    Alignerr
  • Type:
    Hourly Contract
  • Location:

    Remote
  • Commitment: 10–40 hours/week
What You'll Do
  • Translate informal mathematical proofs into Lean 4 (and related proof systems) with an emphasis on clarity, structure, and correctness
  • Analyze generic and domain-specific proofs — identifying hidden assumptions, gaps, and formalizable sub-structures
  • Construct formalizations that push the limits of existing proof assistants, especially in areas where tools struggle or fail
  • Collaborate with AI researchers to design, refine, and evaluate strategies for improving formal verification pipelines
  • Develop clean, readable, reproducible proof scripts aligned with mathematical best practices and Lean idioms
  • Provide expert guidance on proof decomposition, lemma selection, and structuring techniques for formal models
  • Investigate where automated provers break down and articulate precisely why — whether due to complexity, missing lemmas, or library limitations
  • Formalize classical proofs and compare machine-verifiable structures against textbook arguments
  • Create Lean proofs that surface deeper patterns or generalizations implicit in the original mathematics
Who You Are
  • Hold a Master's degree or higher in Mathematics, Logic, Theoretical Computer Science, or a closely related field
  • Have a strong foundation in rigorous proof writing across areas such as algebra, analysis, topology, logic, or discrete mathematics
  • Have hands‑on experience with Lean (Lean 3 or Lean
    4), Coq, Isabelle/HOL, Agda, or a comparable formal proof system — Lean 4 strongly preferred
  • Deeply enthusiastic about formal verification, proof assistants, and the future of mechanized mathematics
  • Able to translate informal mathematical arguments into clean, well‑structured formal proofs independently
  • Thrive working at the intersection of mathematics and computer science, where precision is non‑negotiable
Nice to Have
  • Familiarity with type theory, the Curry-Howard correspondence, and proof automation tools
  • Experience contributing to large-scale formalization projects such as Mathlib
  • Exposure to theorem provers where automated reasoning frequently fails or requires substantial manual scaffolding
  • Prior experience with data annotation, data quality evaluation, or AI training workflows
  • Strong communication skills for explaining formalization decisions, edge cases, and reasoning strategies to interdisciplinary teams
Why Join Us
  • Work directly with world‑leading AI research labs on genuinely frontier problems
  • Fully remote and flexible — structure your work around your life, not the other way around
  • Freelance autonomy with the intellectual depth of high‑stakes mathematical research
  • Gain exposure to how advanced AI models are trained and where formal mathematics fits into that process
  • Contribute to a body of work that maps the boundary of what machines can and cannot yet verify
  • Potential for ongoing collaboration and contract extension as new projects launch
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