About The Role
What if your deep mathematical training could directly shape how AI reasons about truth, proof, and knowledge? We're looking for Formal Verification Scientists to translate advanced mathematical arguments into machine-verifiable Lean 4 proofs — working at the precise intersection of rigorous mathematics and cutting-edge AI research.
This is a fully remote, flexible contract role designed for mathematicians who love precision and thrive at the frontier of what proof assistants can express, capture, and automate.
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 Lean 4 formalizations
Analyze proofs across domains — identifying gaps, hidden assumptions, and formalizable sub-structures
Push the boundaries of existing proof assistants by working on problems that lie beyond current automation capabilities
Collaborate with AI researchers to design and refine formal verification pipelines
Develop readable, reproducible proof scripts aligned with mathematical best practices and Lean idioms
Provide expert guidance on proof decomposition, lemma selection, and structuring strategies for formal models
Investigate where automated provers break down — and articulate precisely why
Uncover deeper patterns and generalizations hidden within classical mathematical 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 a comparable proof assistant — Lean strongly preferred
Genuinely excited about formal verification, proof assistants, and the future of mechanized mathematics
Able to take a dense, informal argument and express it precisely in a form a machine can verify
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 tools
Experience contributing to large‑scale formalization projects such as Mathlib
Exposure to theorem provers where automated reasoning frequently fails or requires manual scaffolding
Prior experience with data annotation, quality evaluation, or AI training workflows
Strong communication skills for explaining formalization decisions, edge cases, and proof strategies
Why Join Us
Work directly on cutting‑edge AI projects alongside leading research labs
Fully remote and flexible — work when and where it suits you
Freelance autonomy with the depth and challenge of meaningful, frontier‑level work
Gain rare exposure to how advanced LLMs are trained to reason about mathematics
Contribute to a growing body of machine‑verifiable mathematical knowledge that will shape AI for years to come
Potential for ongoing work and contract extension as new projects launch
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