Evan Day is a software engineer with a decade of experience focused on AI/ML infrastructure, LLM efficiency, and scalable systems, currently working on YouTube’s ML/infra stack at Google. His background includes GenAI and agentic workflow work at Adobe, backup and database resiliency at Google, and high-frequency trading infrastructure exposure from a stint at Jane Street, reflecting comfort across web-scale and low-latency environments. Trained in industrial engineering and computer science at UC Berkeley and Northeastern, he blends quantitative rigor with practical system design. Fluent in both English and Chinese communities (GitHub bio welcomes technical交流), he often bridges research ideas and production constraints to improve model serving and operational efficiency. An early career pattern shows rapid rotations through top-tier engineering internships, indicating a fast learner who thrives in high-impact, cross-disciplinary teams.
10 years of coding experience
1 year of employment as a software developer
Industrial Engineering & Operation Research, Industrial Engineering & Operation Research at University of California, Berkeley
High School Camp, High School Camp at University of Cambridge
Computer Science, Computer Science at Northeastern University
Contributions:1 PR, 5 pushes, 1 branch in 2 years 9 months
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