# Julia AI Co-Founder for NLU Portfolio

**URL:** <https://discourse.julialang.org/t/julia-ai-co-founder-for-nlu-portfolio/136041>\
**Category:** Jobs\
**Created:** [March 5, 2026, 3:06pm UTC](https://discourse.julialang.org/t/julia-ai-co-founder-for-nlu-portfolio/136041 "2026-03-05T15:06:42Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![JohnGSchwitz](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/johngschwitz/32/221142_2.png) [@JohnGSchwitz](https://discourse.julialang.org/u/JohnGSchwitz)\
**Post date:** [March 5, 2026, 3:06pm UTC](https://discourse.julialang.org/t/julia-ai-co-founder-for-nlu-portfolio/136041/1 "2026-03-05T15:06:42Z")

</div>

## About NLU Portfolio

We’re building three AI-powered platforms (legal document discovery, professional language exchange, educational storytelling) with a Julia-based optimization layer that creates 10-40x performance advantages over Python-based competitors. Our technical moat combines Google Cloud infrastructure, Vector Search 2.0, and proprietary Julia algorithms.

## Position Overview

Part-time (20+ hours/week) remote role developing high-performance optimization algorithms for AI applications. Work directly with founder (MBA + advanced physics background) on platforms targeting $18.5B combined addressable market.

## Compensation

- First 3 months: Equity-only (co-founder track consideration) OR
- If you are STEM OPT 21 hours paid per week for compliance + equity
- After 4 months: Competitive salary + equity with clear advancement path

## Required Qualifications

- Julia proficiency: Demonstrated experience developing and optimizing Julia applications (mandatory)
- Graduate degree: MS/PhD in quantitative field (mathematics, physics, statistics, computational science, economics, engineering)
- Quantitative background: Strong foundation in optimization, numerical methods, or algorithm development

## Responsibilities

- Build optimization layers for legal document search (Disclosure-NLU) and language matching (Lingua-NLU)
- Implement parallel/distributed computing for real-time semantic search across 100K+ documents
- Develop proprietary 47-factor matching algorithm for polyglot professional connections
- Profile and optimize code for 10-40x performance improvements over Python baselines
- Integrate Julia optimization layer with FastAPI + Gemini 2.0 + Vector Search 2.0 stack

## Preferred Qualifications

- Experience with Google Cloud Platform (Vector Search, BigQuery, Vertex AI)
- Familiarity with LLM integration (Gemini, GPT-4) and vector databases (Vector Search 2.0)
- Python experience (for API integration with FastAPI)
- Interest in legal tech, language learning, or educational technology domains

## Why This Role Matters

Your Julia expertise creates our 24-month technical moat:

- 50K Julia developers globally vs. 15M+ Python developers = talent scarcity barrier
- 10-40x performance advantages enable product experiences competitors cannot match
- First-mover advantage on Google Vector Search 2.0 (competitors face $2M+ migration costs)

## Work Environment

- Remote-first (preference for US time zones, we are Mountain Time)
- Direct collaboration with founder on technical architecture decisions
- Small team environment with significant ownership and impact
- Knowledge-sharing culture with documentation emphasis

## To Apply

Send cover letter, resume, and GitHub profile to: [john.schwitz@nebula-nlu.com](mailto:john.schwitz@nebula-nlu.com)

Note: Candidates must demonstrate Julia proficiency through prior coursework, research projects, or professional experience. Quantitative graduate degree desired.