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Christopher Olston

Software Engineer at Google

Christopher Olston is a Stanford CS PhD graduate with a strong background in computer science and machine learning infrastructure.

He has led the ML Infra team at Moloco, overseeing the training of hundreds of models daily and managing a system that serves 6 million queries per second.

Previously, Christopher was a core developer on the Tensorflow stack at Google, contributing to TF-Serving for production machine learning with an impressive load of 180 million queries per second.

His accolades include award-winning research focusing on generalizing Map-Reduce to Directed Acyclic Graphs (DAGs) through projects like Pig and developing co-group primitive.

In addition to his technical expertise, Christopher is an experienced public speaker, delivering keynote speeches and talks at prestigious universities like Berkeley, MIT, and Stanford.

His skill set includes proficiency in programming languages like C++, Python, Java, and Golang, as well as expertise in cloud computing, people management, and technical communication.

Christopher's educational background includes a PhD in Computer Science from Stanford University and a B.S. in Electrical Engineering and Computer Science from the University of California, Berkeley.

Throughout his career, he has held various roles at renowned organizations such as Google, Moloco, Yahoo! Research, and Carnegie Mellon University, showcasing his diverse professional experience.

Highlights

Nov 3 · linkedin

Moloco is hiring for large-scale operational ML. Continuously-trained models doing real-time ad bidding.

Some numbers: 600 billion bid requests per day. 14ms ML inference latency. 460 models trained per day. 4 million training examples processed per second.

Jun 29 · linkedin
Christopher Olston
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Location

Los Altos, California, United States