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Applied Formal Methods Researcher; Lean

Remote / Online - Candidates ideally in
Toronto, Ontario, C6A, Canada
Listing for: Alignerr
Full Time, Remote/Work from Home position
Listed on 2026-01-04
Job specializations:
  • IT/Tech
    AI Engineer, Mathematics, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 70 - 150 CAD Hourly CAD 70.00 150.00 HOUR
Job Description & How to Apply Below
Position: Applied Formal Methods Researcher (Lean 4)

Applied Formal Methods Researcher (Lean
4)

This is an hourly contract position at Alignerr, a company that partners with AI research labs to build and train cutting‑edge AI models. The role is remote and requires 10–40 hours per week, with compensation ranging from $70 to $150 per hour.

Role Overview

We are seeking mathematicians with deep training in rigorous proof construction and hands‑on experience with formal proof languages, especially Lean. This role sits at the intersection of mathematics and computer science, focusing on translating human‑written mathematical arguments into precise, machine‑verifiable formalizations.

What You’ll Do
  • 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.
  • Examples of work you might do:
    • Formalize classical proofs and compare machine‑verifiable structures against textbook arguments.
    • Investigate where automated provers break down and articulate why.
    • Create Lean proofs that reveal deeper patterns or generalizations implicit in the original mathematics.
Requirements
  • 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 mathematics.
  • 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; someone who finds satisfaction in taking a dense, elegant human argument and expressing it in a form that a machine can understand. You appreciate precision, structural beauty, and the challenge of resolving gaps that automated tools cannot yet bridge.

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.

    Other Information

    Referrals increase your chances of interviewing at Alignerr by 2×.

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