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Formal Verification Scientist (Lean 4 & Mathlib)

Alignerr

AI & Data Training Contractor
Remote (Global) $170 – $200/hr May 25, 2026

Job description

Formal Verification Scientist (Lean 4 & Mathlib)

About the Role

What if your deep mathematical training could directly shape how AI understands and reasons about formal proof? We're looking for Formal Verification Scientists to translate advanced human-written mathematics into precise, machine-verifiable Lean 4 formalizations — working at the cutting edge of what proof assistants can express, capture, and automate.

This is a fully remote, flexible contract role for mathematicians who are passionate about formal verification and want their expertise to matter at the frontier of AI research.

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

What You'll Do

  • Translate informal mathematical proofs into clean, structured Lean 4 formalizations with an emphasis on correctness, clarity, and mathematical elegance
  • Analyze proofs across domains — identifying gaps, hidden assumptions, and formalizable sub-structures
  • Construct formalizations that probe the limits of existing proof assistants, especially where automation breaks down
  • Collaborate with AI researchers to design, refine, and evaluate strategies for improving formal verification pipelines
  • Develop readable, 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
  • Investigate where and why automated provers fail — and articulate those boundaries with precision
  • Create Lean proofs that surface 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 systems — Lean 4 strongly preferred
  • Genuinely enthusiastic about formal verification, proof assistants, and the future of mechanized mathematics
  • Able to take dense, informal mathematical arguments and express them in a form a machine can verify
  • Thrive working independently with precision and care

Nice to Have

  • Experience with large-scale formalization projects such as Mathlib
  • Familiarity with type theory, the Curry-Howard correspondence, and proof automation tools
  • Exposure to theorem provers where automated reasoning frequently fails or requires manual scaffolding
  • Prior experience with data annotation, data quality evaluation, or AI training workflows
  • Strong communication skills for explaining formalization decisions, edge cases, and reasoning strategies

Why Join Us

  • Work directly with leading AI research labs on projects at the frontier of formal mathematics and AI
  • Fully remote and flexible — work on your own schedule from anywhere in the world
  • Freelance autonomy with meaningful, intellectually stimulating work
  • Contribute to research that is actively shaping how AI systems reason about mathematics
  • Potential for contract extension as new projects launch
Apply now

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Frequently asked questions

Is Alignerr legitimate?
Yes, Alignerr is a legitimate company listed on RemoWork. We verify all companies on our platform. However, we always recommend doing your own research before sharing personal information or starting work. Check reviews from other users and visit the company's official website for the most up-to-date information.
How do I get started with Alignerr?
To get started, visit Alignerr's official website and look for their careers or sign-up page. Create an account, complete your profile with relevant skills and experience, and apply for available positions or projects. Some companies may require you to pass a qualification test or assessment before you can start working.
Does Alignerr offer remote work?
Yes, Alignerr offers remote work opportunities. Most tasks and positions can be completed from anywhere with a reliable internet connection and a computer or smartphone. Specific location requirements may vary by project or role, so check individual listings for details.
How does Alignerr pay its workers?
Payment methods and schedules vary. Common payment options include PayPal, bank transfers, Payoneer, and other digital payment platforms. Visit Alignerr's official website or check their payment/FAQ section for specific details about payment methods, minimum thresholds, and payout schedules.
What skills do I need to work with Alignerr?
Required skills vary by role and project. Generally, you'll need a reliable internet connection, basic computer literacy, strong attention to detail, and good communication skills. Some positions may require specialized expertise, language proficiency, or technical qualifications. Check individual job listings for specific requirements.
What type of AI work does Alignerr focus on?
Alignerr specializes in AI alignment and model evaluation tasks. Contributors help ensure AI models produce safe, accurate, and helpful outputs by evaluating model responses, identifying errors or biases, and providing human feedback that improves AI behavior and alignment with human values.
Do I need technical AI knowledge to work with Alignerr?
While technical AI knowledge is a plus, many Alignerr tasks are designed for non-technical contributors with strong critical thinking, writing, and analytical skills. The ability to evaluate content quality, identify factual errors, and provide clear feedback is more important than programming expertise for most roles.
How does Alignerr ensure quality in its work?
Alignerr implements multi-layered quality assurance including calibration tasks, consensus scoring between annotators, regular quality audits, and feedback loops. Contributors are expected to maintain high accuracy scores, and ongoing training helps maintain consistent quality standards.
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