A hands-on build guide for implementing a memory-compressed attention engine with key-value caching from scratch in Python. Includes architecture diagrams, production-grade code, and a roadmap to senior-level extensions.
A hands-on build guide for a pure Python HNSW vector index — the data structure powering billion-scale vector search at Meta, Spotify, and Qdrant. Includes runnable code, architecture diagrams, and a senior-level extension roadmap.
A hands-on build guide for a LoRA adapter trainer with fused low-rank gradients and adapter-aware inference in pure NumPy — the kind of project that signals deep ML and systems expertise to hiring managers.
A hands-on guide to building a LoRA fine-tuning engine entirely in NumPy, covering low-rank decomposition, gradient computation, and adapter updates with zero deep-learning framework dependencies.
A hands-on guide to building ‘safe,’ a user safety engine that demonstrates middleware architecture, ML classification, rate limiting, and observability — the kind of systems project that separates junior candidates from senior-level ones.