Formal Verification Scientist (Lean 4 & Mathlib)
Alignerr β’ Remote
Education
Any
Type
Pay Rate
$185/task
Listed
Today
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About this Role
What You'll Do
- Translate informal mathematical proofs into Lean 4 (and related proof systems) with an emphasis on clarity, structure, and correctness
- Analyze generic and domain-specific proofs β identifying hidden assumptions, gaps, and formalizable sub-structures
- Construct formalizations that push the limits of existing proof assistants, especially in areas where tools struggle or fail
- Collaborate with AI researchers to design, refine, and evaluate strategies for improving formal verification pipelines
- Develop clean, readable, reproducible proof scripts aligned with mathematical best practices and Lean idioms
- Provide expert guidance on proof decomposition, lemma selection, and structuring techniques for formal models
- Investigate where automated provers break down and articulate precisely why β whether due to complexity, missing lemmas, or library limitations
- Formalize classical proofs and compare machine-verifiable structures against textbook arguments
- Create Lean proofs that surface deeper patterns or generalizations implicit in the original mathematics
About the Role
What if your deep mathematical expertise could directly shape how the world's most advanced AI systems understand and reason about formal proof? We're looking for Formal Verification Scientists to translate rigorous human-written mathematics into machine-verifiable Lean 4 proofs β working at the very frontier of what proof assistants can express, capture, and automate. This is a fully remote, flexible contract role designed for mathematicians who live and breathe formal reasoning. If you find satisfaction in taking a dense, elegant argument and expressing it in a form a machine can verify β this role was made for you.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10β40 hours/week
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 a comparable formal proof system β Lean 4 strongly preferred
- Deeply enthusiastic about formal verification, proof assistants, and the future of mechanized mathematics
- Able to translate informal mathematical arguments into clean, well-structured formal proofs independently
- Thrive working at the intersection of mathematics and computer science, where precision is non-negotiable
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 substantial 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 to interdisciplinary teams
Why Join Us
- Work directly with world-leading AI research labs on genuinely frontier problems
- Fully remote and flexible β structure your work around your life, not the other way around
- Freelance autonomy with the intellectual depth of high-stakes mathematical research
- Gain exposure to how advanced AI models are trained and where formal mathematics fits into that process
- Contribute to a body of work that maps the boundary of what machines can and cannot yet verify
- Potential for ongoing collaboration 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 expertise could directly shape how the world's most advanced AI systems understand and reason about formal proof? We're looking for Formal Verification Scientists to translate rigorous human-written mathematics into machine-verifiable Lean 4 proofs β working at the very frontier of what proof assistants can express, c
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Frequently Asked Questions
What is the assessment actually like?
Notoriously strict. Alignerr uses TestGorilla for role-specific timed tests β 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 β 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"βthe 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.