Alejandro Saucedo
Alejandro Saucedo is Director of Engineering at Seldon Technologies, where he leads teams of machine learning engineers focused on the scalability and extensibility of machine learning deployment and monitoring products. Alejandro is also the Chief Scientist at the Institute for Ethical AI & Machine Learning, where he contributes to policy and industry standards on the responsible design, development and operation of AI, including the fields of explainability, GPU acceleration, ML security and other key machine learning research areas. With over 10 years of software development experience, Alejandro has held technical leadership positions across hyper-growth scale-ups and has a strong track record building cross-functional teams of software engineers. He is currently appointed as governing council Member-at-Large at the Association for Computing Machinery, and is currently the Chairperson of the GPU Acceleration Kompute Committee at the Linux Foundation.
LInkedin: https://linkedin.com/in/axsaucedo
Twitter: https://twitter.com/axsaucedo
Github: https://github.com/axsaucedo
Website: https://ethical.institute/
Sessions
Identifying the right tools for high performance production machine learning may be overwhelming as the ecosystem continues to grow at break-neck speed. In this session showcase how practitioners can productionise ML models in scalable ecosystems in an optimizable way without having to deal with the underlying infrastructure challenges. We will be taking a GPT-2 HuggingFace model, optimizing it with ONNX and deploying to MLServer at scale using Seldon.