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