Stephen Via
Software Development Engineer II at Amazon Web Services (AWS)
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolStephen Via is a versatile software and firmware engineer with six years of experience spanning embedded systems, low-power sensor networks, machine learning, and cloud services, currently working as an SDE II on AWS SageMaker HyperPod in Seattle. He holds a BS and an accelerated MS in Computer Engineering from Georgia Tech, graduating Summa Cum Laude, and conducted graduate research in computer architecture and multiprocessor networking. His background includes building 802.15.4 APIs and low-power CC13x2 sensor networks at Texas Instruments, radar signal ML work at GTRI, and full-stack prototyping from Raspberry Pi web servers to MATLAB GUIs for hardware validation. Comfortable across the stack from microcontroller C and MIPS to Python-based ML pipelines and large-scale cloud services, he seeks roles that bridge hardware, firmware, and software. A pragmatic problem-solver, he pairs hands-on embedded design with production-oriented cloud engineering, offering a rare blend of applied research experience and shipping product-grade systems.
6 years of coding experience
5 years of employment as a software developer
High School Diploma, High School Diploma at James Hubert Blake High SchoolMaster of Science - MS Computer Engineering, Master of Science - MS Computer Engineering at Georgia Institute of Technology
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (19)
pytorch10
deploying10
python10
machine-learning-models10
jupyter10
data-science10
mxnet10
machine-learning10
inference10
reinforcement-learning10
sagemaker10
amazon-sagemaker10
huggingface10
deep-learning10
mlops10
Programming languages (2)
Github contributions (5)
svia3/sagemaker-python-sdk
Mar 2022 - Aug 2024
A library for training and deploying machine learning models on Amazon SageMaker
Contributions:1 review, 68 pushes, 6 branches in 2 years 5 months
deployingsagemakeramazon-sagemakerpythondeploying-machine-learning
svia3/amazon-sagemaker-examples
Jun 2023 - Jan 2025
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠Amazon SageMaker.
Contributions:22 pushes, 1 branch in 1 year 6 months
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