Nicholas Blaskey
Software Engineer at Amazon Web Services (AWS)
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolNicholas Blaskey is a software engineer with 8 years of experience building cloud-native and distributed systems, currently working on EKS Addons at AWS in Seattle. He has strong backend and DevOps chops demonstrated by contributions to the open-source Determined AI platform—improving cluster management, agent resilience, and security hardening for ML workloads. Prior roles at HPE and Optum involved scalable Java/Spring APIs, Kafka streaming, and AWS infrastructure, showing a practical blend of platform engineering and data-flow systems. Early research and internship work included honeypot development and published analyses on DDoS detection, reflecting a long-standing focus on security and systems-level experimentation. Colleagues know him for shipping pragmatic infrastructure improvements that make complex distributed tooling more reliable and secure.
8 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Marist College
Github Skills (14)
go10
back-end-development10
dockers9
cicd9
kubernetes-pods9
docker9
kubernetes9
mlops8
command-line-interface8
command-line8
cli8
tensorflow7
python7
distributed-training7
Programming languages (5)
Github contributions (5)
determined-ai/determined
May 2022 - Jan 2023
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:886 reviews, 112 commits, 576 PRs in 8 months
Contributions summary:Nicholas contributed to the Determined AI platform by implementing features for cluster management, including requiring admin privileges for specific actions and improving agent reconnection behavior. They also addressed security vulnerabilities by patching Dockerfiles for TensorFlow. Further contributions include adding features to the command-line interface (CLI) for experiment logging, and improvements to deploying and managing infrastructure.
pytorchdata-sciencedeep-learningdistributed-trainingmachine-learning
NicholasBlaskey/determined
May 2022 - Mar 2024
Determined: Deep Learning Training Platform
Contributions:41 PRs, 853 pushes, 181 branches in 1 year 10 months
deep-learningpytorchmachine-learningtraining
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.