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Mathematical Formalization Specialist (Lean / Formal Proof Systems)

Alignerr · Remote · Translation / linguistics

Mathematical Formalization Specialist (Lean / Formal Proof Systems) is an open role at Alignerr, available remotely, with pay listed as $50–$150/hr.

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At a glance

Pay
$50–$150/hrStated by Alignerr
Location
Remote
Listed
Since Oct 4, last confirmed Oct 22

How the pay compares

This role$150
Alignerr median$75
Science / STEM roles median$80
All roles median$60

Higher than 88% of the 117 distinct hourly rates advertised for Science / STEM roles right now. Hourly USD, top of each advertised range, one count per distinct rate. Same method as the Pay Index.

From Alignerr’s listing

“Mathematical Formalization Specialist (Lean / Formal Proof Systems) About the Role What if your deep mathematical training could directly shape how AI reasons, verifies, and understands formal logic?”
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Mathematical Formalization Specialist (Lean / Formal Proof Systems) About the Role What if your deep mathematical training could directly shape how AI reasons, verifies, and understands formal logic? We're looking for mathematicians with hands-on experience in formal proof systems — particularly Lean — to work at the intersection of rigorous mathematics and cutting-edge AI research. This is a fully remote, flexible contract role built for mathematically mature problem-solvers who find satisfaction in translating elegant human arguments into precise, machine-verifiable form. You'll work on proofs that push the boundaries of what automated tools can currently handle — helping map the frontier of formal verification itself. Organization : Alignerr Type : Hourly Contract Location : Remote Commitment : Flexible, task-based 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 Investigate where automated provers break down and articulate why — uncovering complexity, missing lemmas, or insufficient libraries 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, Is

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Frequently asked questions

How do I apply for the Mathematical Formalization Specialist (Lean / Formal Proof Systems) role at Alignerr?

Applications go through Alignerr's own portal - HumanSourcer links to the listing and never collects applications or handles hiring. Alignerr's access model is "Open / self-serve" (Open roles / applications). This listing was first seen here on October 4, 2026 and was still live at the last check.

Is the Mathematical Formalization Specialist (Lean / Formal Proof Systems) role at Alignerr remote?

Yes - Alignerr lists this role as remote.

What does the Mathematical Formalization Specialist (Lean / Formal Proof Systems) role at Alignerr pay?

Alignerr lists this role's pay as $50–$150/hr, quoted from the listing rather than estimated.

What kind of work is Mathematical Formalization Specialist (Lean / Formal Proof Systems)?

Translation / linguistics. AI training, evaluation, coding, writing and specialist review

Is Alignerr a legitimate AI-training platform?

Labelbox expert network - and that relationship is rated "Confirmed" here because it can be checked against labelbox.com rather than taken on Alignerr's word. Confidence describes how well the ownership is evidenced. It is not a rating of how the platform treats the people who work for it, which no public source covers reliably.

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