Darshan Vichhi

I'm a Rust-focused AI Systems Engineer with 3+ years of experience building production-grade backends, encrypted platforms, and from-scratch neural networks. I specialize in implementing LLM architectures (GQA, RoPE, SwiGLU), continual learning systems, and high-performance async backends in pure Rust — with a focus on systems that are fast, memory-safe, and built to scale.

I architected and built Aarambh-AI, a 1.3B-parameter decoder-only LLM built entirely in Rust using Candle — featuring custom CUDA kernels (Flash Attention v2), INT4/GGUF quantization, and DoRA fine-tuning across a 16-crate workspace. The project scales from 25M to 1.3B parameters and includes a full training pipeline (AdamW, cosine scheduling, GRPO reinforcement learning) plus a vision-language extension using a frozen CLIP encoder.

I also designed Manas, a self-growing neural network built from scratch in pure Rust with zero ML framework dependencies — implementing continual learning, dynamic neuron growth, and gradient-gated anti-forgetting mechanisms. On the graphics side, I built Animato, a 17-crate Rust animation engine with GPU-batched compute via wgpu/WGSL, capable of processing 10,000+ tweens per frame.

Beyond AI systems, I've built a zero-knowledge Secure File Sharing Platform (Rust/Axum + Next.js, AES-GCM/RSA encryption, JWT auth) and grown a technical education community to 2,300+ YouTube subscribers through 20+ in-depth tutorials on Rust, backend systems, and AI architecture.

I thrive owning OSS and production work end-to-end — design, implementation, docs, community, and release pipelines — while staying remote-first within a distributed developer community.