San Francisco Bay Area
Northeastern University
M.Sc. and B.Sc., Computer Science
2013 to 2018
The London School of Economics and Political Science (LSE)
Study Abroad, Econometrics, Statistics
2015 to 2015
Peking University
Study Abroad, Chinese Culture and Architecture
2014 to 2014
Homestead High School
2009 to 2013
Focused on building distributed systems that power AI/ML across the company (inference, experimentation, feature computation and serving, training, model lifecycle management, orchestration).Led one of the highest visibility projects (multi-tenant platform attribution) at Lyft in 2020 — presented at Kubecon San Diego 2019. Contributor on several projects related to optimizing workload scheduling, building service-resource knowledge graph, observability, workflow... Focused on building distributed systems that power AI/ML across the company (inference, experimentation, feature computation and serving, training, model lifecycle management, orchestration).Led one of the highest visibility projects (multi-tenant platform attribution) at Lyft in 2020 — presented at Kubecon San Diego 2019. Contributor on several projects related to optimizing workload scheduling, building service-resource knowledge graph, observability, workflow orchestration, and applied machine learning.Interview 100+ candidates and travel to ~every major engineering office as of 2019.
What company does Konstantin Gizdarski work for?
Konstantin Gizdarski works for Lyft
What is Konstantin Gizdarski's role at Lyft?
Konstantin Gizdarski is Software Engineer, Machine Learning Platform
What industry does Konstantin Gizdarski work in?
Konstantin Gizdarski works in the Internet industry.
Who are Konstantin Gizdarski's colleagues?
Konstantin Gizdarski's colleagues are Christian Delahousse, J. Sunday, Ben Lee, Johnny Sparks, Lili Shi, Yi Lu, Tirth Pandya, Bobby Rasmusson, Kevin Stewart, and Carolyn Crimi
📖 Summary
Software Engineer, Machine Learning Platform @ Lyft Focused on building distributed systems that power AI/ML across the company (inference, experimentation, feature computation and serving, training, model lifecycle management, orchestration).Led one of the highest visibility projects (multi-tenant platform attribution) at Lyft in 2020 — presented at Kubecon San Diego 2019. Contributor on several projects related to optimizing workload scheduling, building service-resource knowledge graph, observability, workflow orchestration, and applied machine learning.Interview 100+ candidates and travel to ~every major engineering office as of 2019. San Francisco, California
Introversion (I), Intuition (N), Thinking (T), Perceiving (P)
2 year(s), 0 month(s)
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Likely
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