Worked on backend development and system optimization for the mudler/LocalAI repository, focusing on enhancing model initialization performance. Developed and refined an AVX512-first initialization path for llama-cpp, ensuring that when both AVX512 and AVX2 instruction sets are available, the system prioritizes AVX512 to leverage advanced CPU capabilities. This approach involved reordering the model variant initialization logic in Go to be CPU feature-aware, unlocking potential performance improvements on compatible hardware. The work demonstrated a targeted optimization strategy, aligning software behavior with hardware strengths, and contributed a single feature update without bug fixes during the period, emphasizing efficient, hardware-conscious backend engineering.