{"id":13519,"date":"2025-04-28T10:36:04","date_gmt":"2025-04-28T18:36:04","guid":{"rendered":"https:\/\/live-cometml.pantheonsite.io\/?page_id=13519"},"modified":"2025-06-12T17:01:39","modified_gmt":"2025-06-12T17:01:39","slug":"xandra-zhu","status":"publish","type":"page","link":"https:\/\/www.comet.com\/site\/convergence\/xandra-zhu\/","title":{"rendered":"Xandra Zhu"},"content":{"rendered":"\n
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\u2190 BACK TO EVENT PAGE<\/a><\/p>\n\n\n\n

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Xandra Zhu<\/h1>\n\n\n

Machine Learning Engineer at Uber<\/h2>\n<\/div>\n\n\n\n
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Xandra Zhu is a Machine Learning Engineer on the Michelangelo team at Uber. She develops and delivers generative AI solutions and applied AI frameworks.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

May 13th, 3:05 \u2013 3:35PM ET<\/p>\n\n\n\n

Uber’s Oncall Copilot Accuracy Journey<\/h2>\n\n\n\n
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In today\u2019s fast-paced tech environment, maintaining robust on-call operations is crucial for ensuring the seamless functioning of services. Modern platform engineering teams face the challenge of efficiently managing on-call schedules, incident response, and communication during critical moments, customer support on slack channels. There is productivity loss due to waiting for oncall support. We at Uber solved this problem by building Gen AI Bot to assist oncalls\/users in solving issues and used that experience to Build several components for Gen AI platform.<\/p>\n\n\n\n

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