Lean Engineer

Resolution•Berkeley, CA

10h•Hybrid

About The Position

Resolution is seeking a Lean Engineer to drive their initiative in making the organization proficient with Lean at scale. This role involves providing expertise in Lean and autoformalization, guiding the organization's Lean usage, and strategically planning structures to enhance autoformalization efforts. The primary focus is on ensuring the reliability and effectiveness of AI-generated Lean code, setting conventions, architecture, and review structures, rather than writing Lean code directly. The goal is to accelerate theoretical research, especially as more research is handed off to AI agents.

Requirements

Several years of experience writing Lean and mathlib.
Expertise in Lean community practices (so you can, e.g., explain why one definition, abstraction, or library design works better than another).
Are an AI power user and have experience with autoformalization, and plan to (eventually) never write another line of Lean by hand.
Communicate clearly and enjoy working closely with researchers and engineers.
Have a strong mathematics or theoretical computer science background (Bachelor’s at minimum).
Want to contribute to the alignment of artificial superintelligence.

Nice To Haves

Contributions to mathlib or other substantial Lean libraries.
Experience designing or maintaining large formalization projects.
Experience with Lean tooling, tactic development, metaprogramming, or proof automation.
Experience with AI-assisted mathematical research or automated evaluation.

Responsibilities

Nurture Lean wisdom throughout the organization and be a champion of Lean and autoformalization.
Build and maintain the structures so we can trust agent autoformalization outputs: proof harnesses, code review workflows, etc.
Build and maintain shared Lean libraries with clear definitions, useful abstractions, and a structure that supports review and further (automated) research.
Consolidate overlapping formalizations, resolve inconsistent definitions, and build shared foundations for researchers and agents to reuse.
Improve the reliability, maintainability, and performance of shared Lean projects.
Support researchers in developing custom tools, tactics, and workflows to help them make progress.
Implicit in all of these responsibilities is the understanding that this will be heavily AI-assisted.