Volunteer Technical Mentor for Student Developers, Resume Parsing & NLP Evaluation

Volunteer Technical Mentor for Student Developers, Resume Parsing & NLP Evaluation

The Chamber of Us is looking for a volunteer technical mentor to support student and early-career contributors working on Libelle, our open-source volunteer intake and matching system.

Libelle helps turn high-volume volunteer interest, resumes, and skill information into structured intake data that can support responsible nonprofit project matching. The project currently includes PDF text extraction, a heuristic resume parser, skill normalization/resolver logic, synthetic benchmark data, and benchmark reporting for parser/resolver quality.

We are looking for someone who enjoys mentoring undergraduate students, recent graduates, or early-career developers as they learn how to work on real software systems. This role is less about taking over implementation and more about helping contributors think clearly, scope their work, read benchmark evidence, and grow as engineers.

Current contributor work includes GitHub spikes and issues related to:

• resume parser benchmark analysis
• skill extraction vs resolver/canonicalization failures
• header, section-boundary, and entry-grouping problems
• structured work/project experience extraction using V2 benchmark sections
• Python helper functions for benchmark comparison
• reading CSV/JSON benchmark artifacts and turning findings into practical next steps

A good mentor might help by:

• reviewing a student’s GitHub issue plan before they begin
• helping them break a vague spike into manageable steps
• explaining relevant software engineering, NLP, or evaluation concepts
• helping them interpret benchmark outputs without overclaiming
• suggesting small, testable implementation approaches
• reviewing draft findings or pull requests
• encouraging good engineering habits: evidence, clarity, reversibility, tests, and documentation
• helping contributors build confidence while still holding a high technical standard

Ideal background:

• experience with Python and software engineering workflows
• comfort with GitHub issues, pull requests, JSON, CSVs, and command-line tools
• interest in mentoring undergraduate students, recent graduates, or early-career developers
• familiarity with NLP, information extraction, parsing, search, data systems, or evaluation
• ability to give kind, direct, constructive feedback

Helpful but not required:

• resume parsing or document AI experience
• LLM evaluation experience
• experience with entity resolution, canonicalization, or taxonomy design
• experience teaching, tutoring, TA-ing, coaching, or mentoring technical contributors
• nonprofit or civic-tech experience

This is a flexible volunteer role. A meaningful contribution could be a few asynchronous GitHub comments per month, occasional review of a contributor’s spike write-up, or a short check-in with a student developer when they are stuck.

This is a good fit for someone who wants to help young technical contributors grow through real open-source work while supporting a nonprofit project with practical social impact.