Casey Jao
Software Engineer at Lead
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolCasey Jao is a software engineer with eight years of experience who combines rigorous mathematical training (PhD, UCLA) with hands-on engineering across ML and heterogeneous compute workflows. After postdoctoral research at Berkeley and Toronto, Casey transitioned into industry roles at Agnostiq and DataRobot and now works at Lead, focusing on backend reliability, dependency reduction, and test-driven refactors. They’ve contributed to Agnostiq’s open-source Covalent project, simplifying implementations and removing external dependencies to improve maintainability in complex orchestration code. Based in the New York City area, Casey brings a researcher's attention to correctness and a pragmatic engineer’s drive to ship robust, production-ready systems.
8 years of coding experience
4 years of employment as a software developer
California Institute of TechnologyUniversity of California, Los Angeles
Github Skills (7)
refactoring10
python10
refactor10
testing10
workflow-management9
orchestra8
orchestration8
Programming languages (7)
Github contributions (5)
AgnostiqHQ/covalent
Feb 2022 - Jan 2023
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:222 reviews, 553 commits, 154 PRs in 11 months
Contributions summary:Casey primarily focused on refactoring and improving the Covalent codebase, specifically by removing dependencies and simplifying code implementations. They removed the Sentinel dependency, replacing it with a standard dictionary, and updated the VERSION and CHANGELOG files. Additionally, the user addressed a failing test related to workflow cancellation by increasing the sleep duration. These actions suggest a focus on code maintainability, testing, and reducing external dependencies.
high-performancepythonworkflow-automationwatsonscience
AgnostiqHQ/covalent-aws-plugins
Nov 2022 - Dec 2023
Executor plugins interfacing Covalent with various AWS compute platforms
Contributions:5 reviews, 1 PR, 3 pushes in 1 year 1 month
aws-batchpythonaws-lambdaplatformsaws-compute
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