In this talk we’ll go over tools and techniques to deploy PyTorch in production. The PyTorch organization maintains and supports open source tools for efficient inference like pytorch/serve, job management pytorch/torchx and streaming datasets like pytorch/data. This talk will give an overview of the tools we use both internally at Meta and recommend externally for easy MLops that can scale to hundreds of machines.
Speaker
![](https://plus.qconferences.com/sites/qcon_plus/files/styles/medium/public/pictures/2022-07/mark.jpeg?itok=c13HTq08)
Mark Saroufim
Applied AI Engineer @Meta
Mark is an Applied AI engineer in the Business Engineering group at Meta who spends most of his time maintaining or contributing to github.com/pytorch/{serve,pytorch,torchx,data,examples}. He's passionate about building in the open and even more passionate about online communities.