Applied Formal Methods Researcher (Lean 4)

Alignerr Corp.

Boston (MA)

Remote

USD 83,000 - 152,000

Part time

31 hours ago
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Job summary

Alignerr is seeking Applied Formal Methods Researchers to translate rigorous human mathematics into Lean 4 proofs, pushing the boundaries of automated reasoning. This fully remote, hourly contract role offers flexible hours (10–40 hours/week) and a chance to work at the intersection of mathematics and AI research.

You will translate informal proofs into machine-verifiable formalizations, identify gaps, and collaborate on strategies for formal verification while producing readable proof scripts

Qualifications

  • Hold a Master’s degree or higher in Mathematics, Logic, Theoretical Computer Science, or a closely related field.
  • Strong foundation in rigorous proof writing across algebra, analysis, topology, logic, or discrete mathematics.
  • Hands-on experience with Lean (Lean 3 or Lean 4), Coq, Isabelle/HOL, Agda, or comparable formal systems — Lean strongly preferred.
  • Genuinely enthusiastic about formal verification, proof assistants, and the trajectory of mechanized mathematics.
  • Able to translate dense, informal arguments into clean, precise formal proofs with minimal ambiguity.

Responsibilities

  • Translate informal mathematical proofs into clean, structured, machine-verifiable formalizations in Lean 4
  • Identify gaps, hidden assumptions, and formalizable sub-structures within complex mathematical arguments
  • Construct Lean proofs that probe and expose the current limits of automated proof assistants
  • Collaborate with researchers to design and refine formal verification strategies and pipelines
  • Develop highly readable, reproducible proof scripts aligned with mathematical best practices and Lean idioms
  • Advise on proof decomposition, lemma selection, and structuring techniques for formal models
  • Investigate where and why automated provers break down — and document those findings rigorously
  • Formalize classical results and compare machine-verifiable structures against established textbook arguments

Skills

Lean experience
Proof writing
Mathematical reasoning
Formal methods

Education

Master’s degree or higher

Tools

Lean 4
Lean 3
Coq
Isabelle/HOL
Agda

Job description

About The Role
What if your deep mathematical intuition could directly shape how AI reasons, proves, and understands the world's hardest problems? We're looking for Applied Formal Methods Researchers to translate rigorous human mathematics into machine-verifiable Lean 4 proofs — working at the precise boundary where human mathematical genius meets the limits of automated reasoning.
About The Role
What if your deep mathematical intuition could directly shape how AI reasons, proves, and understands the world's hardest problems? We're looking for Applied Formal Methods Researchers to translate rigorous human mathematics into machine-verifiable Lean 4 proofs — working at the precise boundary where human mathematical genius meets the limits of automated reasoning. This is a fully remote, flexible contract role designed for mathematicians who are passionate about formal verification and hungry to push proof assistants further than they've ever gone.
  • Organization: Alignerr
  • Type: Hourly Contract
  • Location: Remote
  • Commitment: 10–40 hours/week
What You'll Do
  • Translate informal mathematical proofs into clean, structured, machine-verifiable formalizations in Lean 4
  • Identify gaps, hidden assumptions, and formalizable sub-structures within complex mathematical arguments
  • Construct Lean proofs that probe and expose the current limits of automated proof assistants
  • Collaborate with researchers to design and refine formal verification strategies and pipelines
  • Develop highly readable, reproducible proof scripts aligned with mathematical best practices and Lean idioms
  • Advise on proof decomposition, lemma selection, and structuring techniques for formal models
  • Investigate where and why automated provers break down — and document those findings rigorously
  • Formalize classical results and compare machine-verifiable structures against established textbook arguments
Who You Are
  • Hold a Master's degree or higher in Mathematics, Logic, Theoretical Computer Science, or a closely related field
  • Possess 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 comparable formal systems — Lean strongly preferred
  • Genuinely enthusiastic about formal verification, proof assistants, and the trajectory of mechanized mathematics
  • Able to translate dense, informal arguments into clean, precise formal proofs with minimal ambiguity
Nice to Have
  • Familiarity with type theory, the Curry‑Howard correspondence, and proof automation tooling
  • Experience contributing to large‑scale formalization projects such as Mathlib
  • Exposure to theorem provers where automated reasoning frequently fails or requires significant manual scaffolding
  • Prior involvement in data annotation, evaluation, or quality assessment workflows
  • Strong communication skills for articulating formalization decisions, edge cases, and proof strategies
The Ideal Candidate
You’re a mathematically mature problem‑solver who finds genuine satisfaction in taking a dense, elegant human argument and expressing it in a form a machine can fully verify. You appreciate precision, structural beauty, and the intellectual challenge of resolving the gaps that automated tools cannot yet bridge. You’re drawn to frontiers — and this is one of the most exciting in modern mathematics.
Why Join Us
  • Work directly on cutting‑edge AI research projects alongside world‑leading labs
  • Fully remote and flexible — work when and where it suits you
  • Freelance autonomy with the structure of meaningful, high‑impact technical work
  • Gain exposure to how advanced AI models are trained on formal mathematical reasoning
  • Contribute to work that is actively advancing the frontier of mechanized mathematics
  • Potential for ongoing engagement and contract extension as new projects launch
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