Sep 23–26, 2019
Jessica Mong

Jessica Mong
Manager, Machine Learning Engineering, SurveyMonkey

Jessica Egoyibo Mong is an engineering manager on the machine learning engineering (MLE) team at SurveyMonkey. She leads efforts to rearchitect the online serving ML system. Previously, she was a full stack engineer on the billing and payments team, where she built and maintained software to enable SurveyMonkey’s global financial growth and operation; she oversaw the technical talks program, jointly managed the engineering internship program, and co-led the Women in Engineering Group. She’s a 2014 White House Initiative on HBCUs All-Star and a Hackbright (summer 2013) and CODE2040 (summer 2014) alum. She’s served on the leadership team of the Silicon Valley local chapter of the Anita Borg Institute and is a member of /dev/color. Jessica earned a BS in computer engineering from Claflin University in South Carolina. She’s a singer and upcoming drummer, and sings and drums at her church in Livermore, California. In her spare time, she enjoys eating, CrossFit, reading, learning new technologies, and sleeping.

Sessions

11:20am12:00pm Thursday, September 26, 2019
Location: 1A 15/16
Jing Huang (SurveyMonkey), Jessica Mong (SurveyMonkey)
You're a SaaS company operating on a cloud infrastructure prior to the machine learning (ML) era and you need to successfully extend your existing infrastructure to leverage the power of ML. Jing Huang and Jessica Mong detail a case study with critical lessons from SurveyMonkey’s journey of expanding its ML capabilities with its rich data repo and hybrid cloud infrastructure. Read more.

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