Alignerr
Researcher - Lean 4 & Formal Proof Systems

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Researcher - Lean 4 & Formal Proof Systems
Researcher – Lean 4 & Formal Proof Systems (AI Training)
About The Role
What if your deep mathematical expertise could directly shape the future of AI reasoning? We're looking for mathematicians and formal verification specialists to translate sophisticated mathematical proofs into Lean 4 — helping push the boundaries of what machine-verifiable mathematics can express, capture, and automate.
This is a fully remote, flexible contract role. If you find satisfaction in taking a dense, elegant human argument and expressing it in a form a machine can verify, this role was built for you.
Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week
What You'll Do
- Translate informal mathematical proofs into Lean 4 (and related proof systems) with an emphasis on clarity, structure, and correctness
- Analyse generic and domain-specific proofs — identifying gaps, hidden assumptions, and formalisable sub-structures
- Construct formalisations 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 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 — complexity, missing lemmas, insufficient libraries, and beyond
- Create Lean proofs that reveal deeper patterns or generalisations implicit in the original mathematics
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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 math
- Have hands-on experience with Lean (Lean 3 or Lean 4), Coq, Isabelle/HOL, Agda, or comparable systems — Lean strongly preferred
- Deeply enthusiastic about formal verification, proof assistants, and the future of mechanised mathematics
- Able to translate informal mathematical arguments into clean, structured, machine-verifiable proofs
- Mathematically mature and comfortable working independently at the frontier of formal methods


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Nice to Have
- Familiarity with type theory, the Curry-Howard correspondence, and proof automation tools
- Experience with large-scale formalisation projects such as Mathlib
- Exposure to theorem provers where automated reasoning frequently fails or requires manual scaffolding
- Prior experience with data annotation, data quality, or evaluation systems
- Strong communication skills for explaining formalisation decisions, edge cases, and reasoning strategies
Why Join Us
- Work on cutting-edge AI projects alongside leading research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact technical work
- Contribute directly to advancing the capabilities of AI reasoning and formal verification
- Gain exposure to how advanced LLMs are trained on frontier mathematical content
- Potential for ongoing work and contract extension as new projects launch
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