[Women in Infra] Infrastructure for Machine Learning

For our fourth Women in Infrastructure event, we’re going to talk about the cross-functional area of infrastructure and machine learning. Designing infrastructure for machine learning comes with a unique set of challenges, from shipping large data sets to compute nodes; to managing GPU resources; to making large distributed systems accessible to research scientists. We’re excited to have engineers from Microsoft, Twitter, and Yelp speak about their experience in this fast moving field!

6:30-7:00 Doors Open. Food & Drinks
7:00-8:20 Talks!
8:20-9:00 Social & Networking Time

Speakers:
Rita Zhang - Engineer at Microsoft - https://twitter.com/ritazzhang
Bio: Rita is a software engineer at Microsoft on the Azure Cloud Native Compute team building Kubernetes upstream features and features for Azure Kubernetes Service and OpenShift on Azure. Rita is passionate about open source and running distributed workloads at scale.

Talk: Learn how to train and serve ML models at large scale using GPU-enabled Kubernetes clusters on Azure and Kubeflow:

• Training a simple model using GPUs on Kubernetes
• Running Jupyter notebook on Kubernetes
• Monitoring your training on Kubernetes using TensorBoard
• Training a more complex model using distributed TensorFlow

Lydian Lee - Engineer at Yelp - https://www.linkedin.com/in/lydianlee
Bio: Lydian is stepping into her fifth year in the Yelp’s Spam and Abuse Detection team, and has recently become the team's infrastructure lead.

Talk: Lydian's talk will focus on her experiences with the ML model deployment framework her team is using to achieve high maintainability.

Cibele Montez Halasz - Engineer at Twitter - https://twitter.com/cibelemh
Bio: Cibele works at Twitter Cortex, where she builds Twitter’s deep learning platform. She earned her B.S. from Stanford University in Electrical Engineering and Physics and her M.S. from the California Institute of Technology in Electrical Engineering.

Talk: Machine Learning has allowed Twitter to drive engagement, promote healthier conversations, and deliver catered advertisements. Over the past year, we have been working on a new chapter of ML at Twitter by migrating our machine learning platform from Lua Torch to (Python) Tensorflow. This talk will be mainly focusing on the Machine Learning framework we have been developing on top of Tensorflow.

Venue:
The event will be held at Tabletop Tap House, located at 175 4th St. It is kindly sponsored by our friends at Determined AI (https://determined.ai/).

This event is for you if you identify as a women, genderqueer or non-binary, and are interested in infrastructure. Men are welcome to attend as guests!