Valay Dave
Software Engineer at Outerbounds
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolValay Dave is a software engineer with 11 years of experience building resilient backend and cloud infrastructure, currently based in San Francisco and contributing at Outerbounds. He has deep hands-on experience in productionizing AI/ML workflows, including notable backend and DevOps contributions to Netflix’s open-source Metaflow—improving exception handling, storage consistency, and Azure support. His background spans roles from technical architect to cloud infrastructure intern, reflecting a strong practical blend of system design, data integrity, and deployment automation. Valay holds a master's in computer science from Arizona State and began his career delivering full-stack solutions in fast-paced startups. He also pursues side projects like sci-genie.com, showing a continuing interest in applied research tooling and product-focused engineering. Pragmatic and detail-oriented, he excels at turning brittle distributed systems into robust, maintainable platforms.
11 years of coding experience
3 years of employment as a software developer
Bachelor's Degree, Information Technology, Bachelor's Degree, Information Technology at SRM UniversityMaster's degree, Computer Science, Master's degree, Computer Science at Ira A. Fulton Schools of Engineering at Arizona State University
Stackoverflow
1reputation
0reached
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Github Skills (14)
data-storage10
error-handling10
python10
back-end-development10
microsoft-azure9
azure9
mlops9
data-pipeline8
data-pipelines8
machine-learning7
aws6
kubernetes-pods5
gcp5
kubernetes5
Programming languages (11)
Github contributions (5)
Netflix/metaflow
Sep 2021 - Jan 2023
Build, Deploy and Manage AI/ML Systems
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:2 releases, 233 reviews, 88 commits in 1 year 5 months
Contributions summary:Valay primarily contributed to the backend infrastructure and data storage aspects of the Metaflow project. Their work involved addressing exception handling in task execution and error representation, and also fixing inconsistent behavior within the data storage system. Further contributions included the implementation of a decorator hook to add custom packages, and modifications to handle exceptions with non-picklable artifacts, indicating a focus on system robustness and data integrity. Finally, the user's commits touch upon Azure cloud support.
pythonml-infrastructureclir-packagescience
valayDave/metaflow
Feb 2020 - Dec 2022
Build and manage real-life data science projects with ease.
Contributions:1 release, 74 reviews, 1231 commits in 2 years 10 months
pythonsciencelife-datadata-sciencedeep-learning
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