Summary
Chase Adams is a Machine Learning Engineer with a decade of experience building production ML systems and deep learning solutions at companies from Intel Nervana to Google. Based in San Francisco, he combines strong engineering fundamentals from a Computer Engineering BS and an MS in Computer Science with hands-on expertise in TensorFlow, MXNet, CUDA, and C++ across edge-to-cloud workloads. At Intel Nervana he translated cutting-edge research into customer-facing DL solutions, and earlier roles show a pattern of accelerating compute (30x speedups with CUDA) and improving validation quality (20% higher pass rates). He has balanced research, implementation, and operational concerns—shipping models at Google while drawing on low-level GPU and kernel experience from NVIDIA and other internships. Colleagues describe him as pragmatic and detail-oriented, comfortable moving between algorithmic development and production validation. Beyond core ML work, he brings a history of mentoring and community engagement from campus leadership roles to organizing team events.
10 years of coding experience
6 years of employment as a software developer
Classes, Computer Science, N/A, Classes, Computer Science, N/A at Udacity Online Learning
Bachelor of Science (B.S.), Computer Engineering with International Plan and Coop Distinction, 3.78 GPA, Bachelor of Science (B.S.), Computer Engineering with International Plan and Coop Distinction, 3.78 GPA at Georgia Institute of Technology
Japanese