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 a mixture-of-experts router from scratch in Python, covering top-k gating, capacity factor scheduling, and load balancing loss — a CV-worthy project that signals real systems and ML engineering skill.
A hands-on guide to implementing group-wise INT4 quantization for LLaMA-style transformers, covering per-group scale calibration, fused dequantization kernels, and benchmarks that demonstrate real ML-systems engineering skill.
A hands-on guide to building a custom gradient checkpointing engine in PyTorch. This side project demonstrates deep memory management and autograd mastery, making your CV stand out to AI infrastructure roles.
A step-by-step NumPy guide to implementing Flash Attention with tiled multi-head self-attention and causal masking, perfect for a portfolio CV.