Alireza Jazayeri
AI ML Engineering Manager at Apple
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolAlireza Jazayeri is an AI/ML engineering manager based in Seattle with 11 years of experience building cloud-native, data-intensive systems for organizations including Apple, The Climate Corporation, and NASA-focused projects. He combines hands-on expertise in Node.js, Python, Java and Docker with deep AWS knowledge to design reliable, scalable pipelines for ingesting and processing petabytes of satellite, weather, and drone data. At Development Seed he led the team behind NASA’s Cumulus framework and grew the engineering org from a handful to ~20 engineers, demonstrating both technical leadership and hiring acumen. His work balances software architecture and applied ML engineering, shipping production orchestration and data processing at scale. A pragmatic open-source contributor, he has improved usability and build processes for satellite imagery tooling, showing attention to developer experience as well as system reliability.
11 years of coding experience
6 years of employment as a software developer
Master of Science - MS Information Technology, Master of Science - MS Information Technology at Virginia TechBachelor of Arts - BA, Bachelor of Arts - BA at University of Maryland
Persian, English
Github Skills (5)
homebrew10
documentation10
python8
github-ci6
githubaction-workflow6
Programming languages (12)
Github contributions (5)
developmentseed/landsat-util
Aug 2014 - Sep 2014
A utility to search, download and process Landsat 8 satellite imagery
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:16 releases, 17 commits, 119 PRs in 1 month
Contributions summary:Alireza primarily contributed to the project's documentation and build process, making changes to the `README.rst` file. They updated installation instructions, added missing brew commands, and clarified usage examples. In addition, the user modified the `Formula/landsat-util.rb` file to update the sha1 hash and brew link and also incorporated feedback. These updates suggest a focus on improving the user experience and ensuring the project's smooth installation and build processes.
satellite-imagerysatelliteearth-observationsatellite-dataimagery
developmentseed/sentinel-s3
Mar 2016 - Feb 2017
Python libraries for extracting Sentinel-2's metadata from Amazon S3
Contributions:26 PRs, 42 pushes, 10 branches in 10 months
extractionpythonamazonamazon-s3sentinel-2
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