Philipp Schmid
Technical Lead & Open-Source LLM Specialist | Ex-Technical Lead at Hugging Face
Philipp Schmid is a leading AI engineer and open-source educator who served as Technical Lead at Hugging Face, driving partnerships with AWS, Google Cloud, and enterprise infrastructure providers. Philipp is widely followed for his production guides and open-source cookbooks on fine-tuning, serving, and evaluating open-weight foundation models.
Areas of focus
Professional niches
Proof of Work
Serverless LLM Inference Optimization & TGI Deployment Blueprint
An end-to-end production deployment playbook detailing continuous batching, PagedAttention integration, and tensor parallelism configurations using Text Generation Inference (TGI) on cloud infrastructures.
Production throughput benchmarks rely on dedicated cloud GPU clusters (NVIDIA A10G/A100); cold start latency must be managed in serverless scaling.
Context: Optimized for LLaMA-2/3, Mistral 7B, and Mixtral 8x7B running on TGI and vLLM runtimes.
View missionProduction Open-Source LLM Fine-Tuning & Evaluation Cookbook with TRL and vLLM
Comprehensive production blueprint demonstrating automated DPO, SFT, and vLLM deployment pipelines with continuous evaluation harnesses on AWS SageMaker and Kubernetes.
Requires careful GPU memory budget tuning when scaling multi-GPU distributed tensor parallelism across heterogenous cluster nodes.
Context: Hugging Face TRL, vLLM, PyTorch, Ray, and AWS SageMaker.
View mission