Dylan Peck
Software Development Engineer at Amazon Web Services (AWS)
California, United States
Summary
🤩
Rockstar🎓
Top SchoolDylan Peck is a Software Development Engineer at AWS with seven years of experience building cloud-native systems, VR/AR experiences, and ML-enabled applications. He previously architected training labs and managed programs at Google, and has hands-on experience deploying TensorFlow models to GCP AI Platform and resolving real-world dependency and deployment issues. Comfortable in Unity/C# for realistic physics simulation and reinforcement learning workflows, Dylan blends game development and machine learning expertise with cloud architecture. His background in professional audio production and a master's in contemporary performance give him a rare cross-disciplinary edge for immersive media and spatial audio applications. Based in California, he combines production-grade attention to detail with practical DevOps instincts to take prototypes into production.
7 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Jazz/Jazz Studies, Bachelor's degree, Jazz/Jazz Studies at California State University, NorthridgeMasters, Contemporary Performance (Production Concentration), Masters, Contemporary Performance (Production Concentration) at Berklee College of MusicComputer Science, Computer Science at 42 Silicon Valley
Github Skills (15)
google-cloud-ml-engine10
jupyter-notebook10
google-cloud-platform10
machine-learning10
tensorflow10
python10
gcloud10
ml10
gcp10
ml-deployment9
data-analysis9
ai-platform9
continuous-deployment9
pandas8
h5py8
Programming languages (8)
Github contributions (5)
GoogleCloudPlatform/training-data-analyst
Jun 2020 - Dec 2022
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 59 commits, 44 PRs in 2 years 5 months
Contributions summary:Dylan added several notebooks related to predicting housing prices using TensorFlow and Cloud ML Engine. They moved notebooks from an external repository, integrated and updated datasets from Google Cloud Storage, and also incorporated cloud platform commands, including AI Platform model deployment and version management. Further contributions include upgrading or downgrading of dependencies like `h5py` to facilitate correct environment configuration, indicating focus on model deployment and cloud infrastructure interaction within a machine learning context.
gcpgoogle-cloud-platformgoogle-cloudtraining
dylanmpeck/Beat-Virus
Feb 2020 - May 2024
Contributions:38 pushes, 1 branch in 4 years 3 months
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