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Mathematics alignerr

Mathematical Formalization Specialist (Lean / Formal Proof Systems)

Alignerr Remote Posted 0 days ago

Education

Any

Type

Pay Rate

$100/task

Posted

0d ago

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About this Role

What You'll Do

  • Translate informal mathematical proofs into Lean (and related proof systems) with an emphasis on clarity, structure, and correctness
  • Analyze proofs across mathematical domains — identifying gaps, hidden assumptions, and formalizable sub-structures
  • Construct formalizations that test the limits of existing proof assistants, especially where automated tools struggle or fail
  • Collaborate with AI researchers to design, refine, and evaluate strategies for improving formal verification pipelines
  • Develop clean, reproducible proof scripts aligned with mathematical best practices and proof assistant idioms
  • Provide expert guidance on proof decomposition, lemma selection, and structuring techniques for formal models

About the Role

What if your deep mathematical training could directly shape the future of AI reasoning? We're looking for mathematicians with hands-on experience in formal proof systems — especially Lean — to tackle problems that sit beyond the reach of automated tools. This is a fully remote, flexible contract role at the intersection of mathematics and computer science. You'll work on genuinely hard problems, translating rigorous human arguments into machine-verifiable formalizations that help map the frontier of what proof assistants can express, capture, and automate.

  • Organization: Alignerr
  • Type: Hourly Contract
  • Location: Remote
  • Commitment: Flexible, task-based

Sample Work You Might Do

  • Formalize classical proofs and compare machine-verifiable structures against textbook arguments
  • Investigate where automated provers break down — and articulate precisely why (complexity, missing lemmas, insufficient libraries, etc.)
  • Write Lean proofs that reveal deeper patterns or generalizations implicit in the original mathematics

Who You Are

Required: Nice to Have:

  • Master's degree or higher in Mathematics, Logic, Theoretical Computer Science, or a closely related field
  • Strong foundation in rigorous proof writing 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 formal proof systems — Lean strongly preferred
  • Genuine enthusiasm for formal verification, proof assistants, and the future of mechanized mathematics
  • Ability to translate dense, informal mathematical arguments into clean, structured formal proofs
  • 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
  • Strong communication skills for articulating formalization decisions, edge cases, and reasoning strategies

The Ideal Candidate

You're a mathematically mature problem-solver who finds genuine satisfaction in taking a dense, elegant argument and expressing it in a form a machine can understand. You appreciate precision, structural beauty, and the intellectual challenge of resolving gaps that automated tools cannot yet bridge. You don't just do mathematics — you think carefully about how mathematics is done.

Why Join Us

  • Work on cutting-edge AI research projects alongside leading research labs
  • Fully remote and flexible — work when and where it suits you
  • Freelance autonomy with the structure of meaningful, intellectually stimulating work
  • Contribute directly to advancing the reliability and reasoning capabilities of next-generation AI
  • Potential for ongoing work and contract extension as new projects launch

Requirements

  • Fluent proficiency in English (Written & Verbal)
  • Reliable high-speed internet connection
  • Bachelor's degree or equivalent professional experience
  • Demonstrated expertise in Mathematics

Compensation Analysis

What if your deep mathematical training could directly shape the future of AI reasoning? We're looking for mathematicians with hands-on experience in formal proof systems — especially Lean — to tackle problems that sit beyond the reach of automated tools. This is a fully remote, flexible contract role at the intersection of mathematics and computer

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Frequently Asked Questions

What is the assessment actually like?

Notoriously strict. Alignerr uses TestGorilla for role-specific timed tests — a blank coding environment for engineers, rigorous grammar and fact-checking for writers. There is almost no hand-holding. The critical catch: this is essentially a one-shot process. Fail or abandon the assessment, and you are typically locked out of that role permanently with no option to retake.

How quickly can I start earning after I pass?

Not immediately. Even after passing the assessment and completing identity verification (via Persona) and billing setup (via Deel), you may sit in a waiting pool for weeks or months. You only start earning when a project matching your specific skills launches and you are officially assigned. Do not plan around Alignerr income until you are actively on a project.

Is there a community?

Yes — and it is one of Alignerr's genuine strengths. Once assigned to a project, you are added to Slack channels where you can ask questions, get rubric clarifications from admins, and talk to other AI trainers. This is rare in AI training and makes a real difference when guidelines are ambiguous or change mid-project.

Is this traditional consulting?

Not exactly. You act as a "Teacher" for advanced AI. Instead of client deliverables, you are given complex scenarios to evaluate. You grade the AI's logic, correct its hallucinations, and provide expert-level reasoning. Your job is to train the model to think like you do.

Why is the pay so high?

This role requires deep, verified expertise. General knowledge isn't enough; the model is specifically being trained on "edge cases"—the rare, difficult, or highly technical nuances that only a senior professional would know.

What is the workload like?

This is cognitive, deep work. Unlike simple data labeling, you might spend 45-60 minutes on a single task, researching citations or verifying complex calculations. Quality is prioritized over speed.

What is the barrier to entry?

Alignerr is known for difficult technical assessments. You must pass a timed test in your specific domain (e.g., Python, Physics, or Language) before you are eligible for any paid projects.