I'm an AI engineer focused on building production-grade LLM systems and scalable reinforcement learning frameworks. I love turning cutting-edge research into clean, usable code.
- 🔭 Currently working on distributed LLM training, model growth, and high-performance inference engines
- 🌱 Exploring RL for reasoning, MoE scaling, and NPU/CUDA unified stacks
- 💡 Believer in learning by building — most repos are educational but production-oriented
| Project | Description |
|---|---|
| ScaleTorch | 5D distributed training framework (DP, PP, CP, EP, TP) on PyTorch with NPU/CUDA support. |
| llm-grow | Grow larger models from existing checkpoints: depth, width, and MoE expert expansion with function-preserving guarantees. |
| mini-sglang | Lightweight educational implementation of SGLang (~4k lines) with PagedAttention, RadixCache, CUDA/NPU Graph, and OpenAI-compatible API. |
| mini-vLLM | A compact implementation of vLLM, demystifying modern LLM serving systems. |
| LLamaTuner | Easy and efficient finetuning pipelines for LLMs. |
| LLMEval | A modular framework to evaluate LLMs across tasks and settings. |
LLM Training & Serving
Distributed & Systems
API & Data Formats
Languages & Core
- Email: jianzhnie@gmail.com
- Homepage: jianzhnie.github.io
- Blog: jianzhnie.github.io/llmtech
- ZhiHu: zhihu.com/column/fengnie
- Hugging Face Org: huggingface.co/GaussianTech
- LinkedIn: linkedin.com/in/jianzheng-nie-2749b7156
- Ask me about: statistics, machine learning, LLMs, and RL.
- ❤️ Sponsor me on GitHub