# Ryan McCormick > Engineering Manager @ NVIDIA Dynamo Location: San Francisco Bay Area, United States Profile: https://flows.cv/ryanmccormick Solving interesting™️ problems in AI Inference. ## Work Experience ### Engineering Manager @ NVIDIA Jan 2026 – Present | San Francisco Bay Area ### Senior Software Engineer @ NVIDIA Jan 2022 – Jan 2026 Dynamo / Triton Inference Server GitHub: - https://github.com/ai-dynamo - https://github.com/triton-inference-server/ ### Software Engineer @ NVIDIA Jan 2019 – Jan 2022 | Santa Clara, California NVEX ### Software Engineering Intern @ NVIDIA Jan 2019 – Jan 2019 | Santa Clara, California NVEX ### HackBU President @ Binghamton University Jan 2018 – Jan 2019 - Organized Binghamton University's annual hackathon, HackBU 2019 - Ran weekly technical workshops on Computer Science topics - Raised funds and sponsorships for club events and hackathons ### Software Engineering Intern @ Citi Jan 2018 – Jan 2018 | Jersey City, New Jersey Worked with Citi's Options Market Making (OMM) team to enhance performance of their Ultra Low Latency trading across multiple exchanges through Machine Learning and Big Data analytics using C++, Python, and KDB/Q. Used Keras and XGBoost libraries to implement ML models for prediction and recommendation of trading opportunities. ### Deep Learning Research Intern @ Air Force Research Laboratory Jan 2017 – Jan 2017 | Dayton, Ohio Area Researched layer-by-layer analysis of convolutional neural networks in order to demystify some of the "magic" that makes neural networks so powerful, and discover ways to improve them. The analysis was based off an approach previously written in MATLAB as described in this paper: http://ieeexplore.ieee.org/document/7965929 The approach was to start at the output layer of a Convolutional Neural network on an image classification problem for example, and for each class in the output layer, correlate the activations of the previous layer with this class output neuron above a given threshold, and repeat this process for every layer of the network in order to make a prediction from each layer of the network and gauge it's impact and standalone accuracy. ### Research Assistant @ Binghamton University Jan 2017 – Jan 2017 | Graphics and Image Computing Lab (GAIC) Helped a research group of Freshman get started with Keras and TensorFlow for research in 3D Facial Recognition using Python. ### Physics Teaching Assistant @ Binghamton University Jan 2016 – Jan 2016 Conducted lab experiments to help students further understanding of concepts taught in lecture. ### Freshman Research Immersion Program @ Binghamton University Jan 2015 – Jan 2016 One of 30 students selected from the Class of 2019 to conduct research with a member of Binghamton's faculty during the first three semesters of university. My research stream was in the field of Image Acoustics and Signal Analysis, using C++, OpenCV, CMake, Microsoft Visual Studio, Leap Motion, and Microsoft Kinect. My research narrowed down to the Computer Vision field under published faculty member Dr. Shaun Canavan, specifically Automatic Sign Language Recognition. ## Education ### Bachelors of Science in Computer Science Binghamton University Jan 2015 – Jan 2019 ### Computer Science Stanford University Jan 2020 – Jan 2021 ### Bachelors of Arts in Mathematics Binghamton University Jan 2015 – Jan 2019 ## Contact & Social - LinkedIn: https://linkedin.com/in/rmccorm4 --- Source: https://flows.cv/ryanmccormick JSON Resume: https://flows.cv/ryanmccormick/resume.json Last updated: 2026-03-23