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Ellie Talius
Research Engineer @ Google DeepMind
Ellie Talius is a Research Engineer at Google DeepMind, where she is involved in the development and application of advanced artificial intelligence technologies. She has a background in engineering and research, having graduated from Stanford University, which is noted for its rigorous academic programs and contributions to technology and science.
Her LinkedIn profile indicates that she has over 500 connections and highlights her experience at Google DeepMind, where she joined the Applied team after completing her studies in June 2021.24 Ellie is based in Mountain View, California, and previously held an internship at Amazon before transitioning to her role at DeepMind.34
In addition to her professional achievements, Ellie has also been recognized for her academic performance, earning accolades such as being on the Pac-12 Academic Honor Roll during her time as a student-athlete.1
Highlights
I couldn’t be more excited to announce that I will be joining DeepMind as a Research Engineer on the Applied team after graduating this June! Thank you so much to the DeepMind recruiters and my friends and family for their help through this process!
(PS: I first learned about DeepMind when I watched the AlphaGo documentary before even going to Stanford University or knowing I wanted to study CS. It’s wild to think that that's where I would end up 4 years later!)
I'm excited to share some updates from the last few months!
I just finished up a SWE internship at Meta on the AI Infra Feature Privacy Team. I learned so much while working to ensure privacy compliance of features through creating a validation pipeline and designing a new integration testing framework. Thank you to the entire AI Infra Feature Privacy Team for all their help, and especially Thilak Raj Balasubramanian for his mentorship and Arnold Pereira and Ilina Mitra for their leadership.
Additionally, I'm excited to share that our work, CheXzero was published in Nature Portfolio today! We demonstrated detection of diseases in chest x-ray images at the level of radiologists without using any explicitly labelled data. Working with this team of Ekin Tiu, Pujan Patel, Pranav Rajpurkar, Curtis Langlotz and Andrew Ng at Stanford University and Harvard Medical School has been incredible and such a great learning experience. https://lnkd.in/di4DiuSD
And lastly, as I begin my search for full time roles, I'm so excited to be attending the Grace Hopper Conference later this month. I'm looking forward to connecting with both sponsors and other attendees, so let me know if you'll be attending!
#meta #internship2022 #ghc22
