Researcher - Lean 4 & Formal Proof Systems

Alignerr Corp.; Birmingham; Remote; GBP 96.000 - 152.000; Teilzeit

Zusammenfassung

Alignerr seeks researchers to translate advanced mathematical proofs into Lean 4 formalizations, pushing the boundaries of automated reasoning. You will work remotely on 10–40 hours per week, translating dense arguments into machine-verifiable proofs and collaborating with AI researchers to improve verification pipelines.

Ideal candidates hold a Master’s or higher in mathematics or related fields, with strong proof-writing skills and experience in Lean, Coq, Isabelle/HOL, or Agda.

Qualifikationen

• Master's degree or higher in Mathematics, Logic, Theoretical Computer Science, or related field.
• Strong foundation in rigorous proof writing and formal verification.
• Experience with Lean 4 preferred; familiarity with alternative proof assistants is valuable.

Aufgaben

• Translate informal proofs into machine-verifiable Lean 4 formalizations.
• Analyze proofs to identify hidden assumptions and gaps.
• Develop readable, reproducible proof scripts in Lean idioms.
• Collaborate with AI researchers to refine verification strategies and pipelines.
• Explain proof strategies and edge cases to team members.

Kenntnisse

Formal reasoning

Proof writing

Independent working

Lean ecosystem familiarity

Ausbildung

Master's degree or higher in Mathematics, Logic, or TCS

Tools

Lean 3/4

Coq

Isabelle/HOL

Agda

Jobbeschreibung

Researcher – Lean 4 & Formal Proof Systems (AI Training)

About The Role

What if your deep mathematical expertise could directly shape how AI reasons, proves, and understands the most rigorous structures in all of science? We're looking for mathematicians and formal verification specialists to translate sophisticated mathematical arguments into machine-verifiable Lean 4 proofs — working at the absolute frontier of what proof assistants can express and automate.

This is a fully remote, flexible contract role designed for researchers who love precision, structural elegance, and the intellectual challenge of pushing formal systems beyond their current limits.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Translate informal mathematical proofs into clean, correct, machine-verifiable Lean 4 formalizations
• Analyze proofs across domains — identifying hidden assumptions, gaps, and formalizable substructures
• Construct formalizations that test the boundaries of existing proof assistants, especially where automation breaks down
• Collaborate with AI researchers to design and refine formal verification strategies and pipelines
• Develop readable, reproducible proof scripts aligned with mathematical best practices and Lean idioms
• Provide expert guidance on proof decomposition, lemma selection, and structuring techniques
• Investigate where automated provers fail — and articulate precisely why (complexity, missing lemmas, library gaps, etc.)
• Formalize classical and advanced proofs that reveal 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 comparable formal systems — Lean 4 strongly preferred
• Are genuinely enthusiastic about formal verification, proof assistants, and the future of mechanized mathematics
• Can translate dense, informal mathematical arguments into precise, structured formal proofs
• Are self‑directed and comfortable working independently on complex, open‑ended problems

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 in settings where automated reasoning frequently fails or requires manual scaffolding
• Prior experience with data annotation, data quality, or AI evaluation systems
• Strong communication skills for explaining formalization decisions, edge cases, and proof strategies

Why This Role Stands Out

• Work directly at the intersection of advanced mathematics and cutting‑edge AI research
• Collaborate with world‑leading AI research teams and labs
• Gain deep exposure to how frontier large language models are trained and evaluated
• Fully remote and asynchronous — work on your own schedule, from anywhere
• Freelance autonomy with the substance of genuinely meaningful, high‑impact research work
• Potential for ongoing contract extension as projects grow and evolve