Achal Shah
Software Engineer at Delphina
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolAchal Shah is a software engineer with 12 years of experience building scalable ML and data platforms, currently leading development at Delphina to create a context layer for data. He has held technical leadership roles at Tecton and Reddit, and earlier helped scale Uber’s Michelangelo inference platform and Amazon’s fulfillment systems, giving him deep expertise in low-latency serving, realtime ingestion, and production ML workflows. An active open-source contributor, Achal has made substantive backend and DevOps contributions to Feast—the popular open-source feature store—improving CLI timezone handling, batch materialization, and data validation. He combines hands-on engineering with team leadership, shipping secure, high-throughput systems used for frequent model retraining and real-time feature computation. Based in Seattle, Achal’s background in both infrastructure and ML product primitives makes him adept at turning complex data problems into reliable production services.
12 years of coding experience
12 years of employment as a software developer
Bachelor of Technology, Computer Engineering, Bachelor of Technology, Computer Engineering at Institute of Technology, Nirma UniversityMaster of Science and Engineering, Computer and Information Science, Master of Science and Engineering, Computer and Information Science at University of Pennsylvania
English, Hindi, Gujarati, Kannada
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
pytest10
python10
cli10
data-validation9
machine-learning9
big-data9
mlops8
git8
version-control8
data-engineering8
data-science8
cicd8
ml8
Programming languages (12)
Github contributions (5)
feast-dev/feast
May 2021 - Jan 2023
The Open Source Feature Store for AI/ML
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:7 releases, 1195 reviews, 255 commits in 1 year 8 months
Contributions summary:Achal made several contributions focused on improving the command-line interface (CLI) and materialization processes of the Feast feature store. Their work involved incorporating timezone awareness in the CLI, enhancing test suite features (like adding tests), and creating code to support a new batch materialization engine. Additionally, the user addressed issues related to data validation, including ensuring that relevant columns exist in the entity dataframes, and the handling of potential errors related to remote storage.
pythondata-qualitydata-sciencemlmachine-learning
achals/dotfiles
Apr 2015 - Mar 2025
Contributions:27 pushes, 1 branch in 10 years 1 month
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