Systems

Build a Minimal GPT Training Loop with Rotary Positional Embeddings

Implement a minimal GPT training loop with rotary positional embeddings from scratch to demonstrate real systems skill to hiring managers.

A diagram of a context window manager pruning tokens.

Memory‑Efficient Context Window Manager with Attention‑Guided Token Pruning

This project delivers a runnable Python library that compresses LLM context windows by scoring token importance with attention and dropping low‑impact tokens, demonstrating practical systems and ML engineering.

Abstract representation of a graph of vectors

Building a HNSW Vector Index from Scratch in Python

This guide walks you through building a hierarchical navigable small world vector index in pure Python. You’ll learn brute‑force construction, greedy graph search, and how to extend it for production.

Building a Paged KV Cache Allocator with Continuous Batching in Pure Python

This project demonstrates memory management, concurrent request scheduling, and low-level allocator design—all core skills for backend and ML infrastructure roles.

A schematic of a mixture-of-experts model routing tokens to experts.

Build a Minimal Mixture-of-Experts Inference Engine in Pure Python

Implement a minimal mixture-of-experts inference engine from scratch in Python, demonstrating systems thinking, custom loss functions, and production-ready patterns.