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Mathematician – Formalization & AI Foundations (Remote Contract)

Alignerr · Remote · Translation / linguistics

Mathematician – Formalization & AI Foundations (Remote Contract) is an open role at Alignerr, available remotely, with pay listed as $170–$200/hr.

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At a glance

Pay
$170–$200/hrStated by Alignerr
Location
Remote
Listed
Since Oct 4, last confirmed Oct 22

How the pay compares

This role$200
Alignerr median$75
Science / STEM roles median$80
All roles median$60

Higher than 94% 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

“Mathematician – Formalization & AI Foundations (Remote Contract) About the Role What if your deep knowledge of formal mathematics could directly shape how the most advanced AI systems in the world reason, prove, and think?”
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Mathematician – Formalization & AI Foundations (Remote Contract) About the Role What if your deep knowledge of formal mathematics could directly shape how the most advanced AI systems in the world reason, prove, and think? We're looking for mathematicians with a passion for rigorous proof and formal systems to help build the mathematical foundations that frontier AI depends on. This is a fully remote, flexible contract role working at the intersection of pure mathematics, logic, and cutting-edge AI research. Poland has one of the world's most celebrated mathematical traditions — rooted in logic, set theory, and foundations. If you know your way around Lean 4 and want to apply that tradition to frontier AI, this role is built for you. Organization : Alignerr Type : Hourly Contract Location : Remote Commitment : 10–40 hours/week What You'll Do Formalize advanced mathematical arguments and theorems in Lean 4, spanning a wide range of mathematical disciplines Contribute to the growth and quality of large-scale formal mathematical libraries, including mathlib Construct clean, readable, and well-structured formal proofs that translate informal mathematical reasoning into rigorous machine-checkable form Audit and verify existing formal proofs for correctness, completeness, and logical integrity Work at the frontier of AI research, helping train the next generation of mathematically capable language models Who You Are Hold a Master's degree or PhD in Mathematics or a closely related field Possess a strong background in rigorous mathematical proof writing and logical reasoning Have hands-on experience with formal proof assistants — Lean 4 strongly preferred Can fluently translate informal mathematical ideas into structured, machine-verifiable formal proofs Self-motivated and comfortable working independently in a remote, asynchronous environment Nice to Have Prior experience with proof verification, theorem proving, or mathematical formalization projects Familiarity with mat

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Frequently asked questions

How do I apply for the Mathematician – Formalization & AI Foundations (Remote Contract) 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 Mathematician – Formalization & AI Foundations (Remote Contract) role at Alignerr remote?

Yes - Alignerr lists this role as remote.

What does the Mathematician – Formalization & AI Foundations (Remote Contract) role at Alignerr pay?

Alignerr lists this role's pay as $170–$200/hr, quoted from the listing rather than estimated.

What kind of work is Mathematician – Formalization & AI Foundations (Remote Contract)?

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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