David Nola
Deep Learning Solutions Architect at NVIDIA
California, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Nola is a Deep Learning Solutions Architect at NVIDIA with 11 years of experience building scalable ML systems and production workflows. He combines a strong academic foundation—MS in Computer Science (UCLA) and a summa cum laude BS in Finance and Computer Science—with hands-on experience designing distributed, cloud-scaling ML pipelines (including an automated seizure-detection system and hybrid EC2/local processing for 70GB datasets). At NVIDIA he has progressed from intern to solutions architect, helping bridge research models and production deployment for real-world performance and throughput. Earlier roles in release engineering and analytics show he’s equally comfortable building CI/CD and build-cluster infrastructure as tuning models, and his background in finance and leadership hints at an analytical, product-minded approach to technical problems.
11 years of coding experience
3 years of employment as a software developer
Bachelor of Science, Finance and Computer Science (Double Major), Summa Cum Laude, Grade Point Average: 3.93 / 4.0, Bachelor of Science, Finance and Computer Science (Double Major), Summa Cum Laude, Grade Point Average: 3.93 / 4.0 at Santa Clara University Leavey School of BusinessMaster of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at University of California, Los Angeles
Stackoverflow
1reputation
76reached
0answers
1question
Github Skills (98)
python10
deep-learning10
data-science10
tensorrt10
nvidia10
music-visualizer10
theano10
pytorch10
visualizer10
machine-learning10
optimizer9
sdk9
latency9
jax9
music9
Programming languages (6)
Github contributions (5)
dnola/145_whats_cooking
Nov 2015 - Dec 2015
Contributions:2 PRs, 25 pushes, 1 branch in 24 days
dnola/dn_docker_helpers
Jul 2016 - Sep 2016
Contributions:23 pushes, 1 branch in 2 months
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