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Sheng Lundquist has a diverse work experience in the field of machine learning and research. They started their career as a Student Researcher at Los Alamos National Laboratory in 2012. They then moved on to work as a Graduate Student Researcher at New Mexico Consortium from 2012 to 2019. In 2012, they also worked as a Contract Researcher at DARPA, where they were part of a team that developed the Locally Competitive Algorithm (LCA) for the Defense Advanced Research Agency (DARPA) and George Mason University's (GMU) Innovation House.

In 2016, Sheng worked as a Graduate Research Assistant at Los Alamos National Laboratory. The following year, they joined Mad Street Den as a Computer Vision Machine Learning Engineer. In 2018, they interned as a Systems Engineering Intern at cPacket Networks.

From 2019 to 2023, Sheng worked at cPacket Networks as a Senior Machine Learning Engineer. They are currently employed at DELV (formerly Element Finance) as a Senior Research Engineer/Scientist, specializing in machine learning.

Overall, Sheng Lundquist's work experience demonstrates a strong background in machine learning, research, and engineering.

Sheng Lundquist obtained a Bachelor of Science (BS) degree in Computer Science from the New Mexico Institute of Mining and Technology between 2008 and 2013. In 2015, Sheng Lundquist enrolled at Portland State University and completed a Doctor of Philosophy (Ph.D.) degree in Computer Science in 2020.