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I am a Technical Lead at Hugging Face, leading our collaboration and partnerships with major cloud providers like AWS, Google Cloud, Azure, and Cloudflare.

At Hugging Face, I have been instrumental in driving the company's growth through our Cloud and Hardware offerings. I serve as the Technical/Engineering Lead for our partnerships with AWS (SageMaker & Neuron), Google (Vertex AI & GKE), Azure (AzureML), and Cloudflare and created Hugging Face Inference Endpoints the easiest way to deploy LLMs into production.

If I'm not putting Transformers and Generative AI models into services or production, I'm collaborating with our open-source and science teams to make LLMs more accessible. I am currently focusing on LLMs using RLHF for enterprise and business use cases.

7+ years ago, I started my passion for cloud concepts and machine learning. Since then, I have leveraged this passion to design and implement cloud-native machine learning architectures for fin-tech and insurance companies. In recognition of my expertise in this field, I became the first German AWS Machine Learning Hero in June 2021.

In addition to my work at Hugging Face, I engage in evangelism and advocacy efforts, sharing my knowledge and insights through research publications, blog posts on LinkedIn, and posts on X (formerly Twitter).

I write about all the stuff i am working under philschmid.de.

Below is a list of Technologies (mostly open source frameworks, libraries, and languages) I regularly use and enjoy working with. If you want to see more what I do or have done, check out my GitHub.

🤖 Machine Learning
Transformers, PyTorch, Scikit-Learn, Langchain, Weights & Bias, Deepspeed, TensorRT, Triton, ONNX.

☁️ Cloud
AWS, GCP, Azure, Kubernetes, Kubeflow, Docker, Terraform, Github Actions, CDK.

🏗️ Non-ML
Rust, Next.js, Svelte, Tailwind, FastAPI, Shadcn, React, GRPC.