Dan Davydov is a Sr. Machine Learning Engineer based in San Francisco with 12 years of experience building production ML and backend systems across high-scale consumer platforms. He has held progressive engineering and tech lead roles at Twitter and Airbnb, now driving applied ML work at Twitter since 2018. Comfortable across the stack, Dan combines model-driven solutions with pragmatic backend and DevOps improvements—evidenced by contributions to Apache Airflow where he improved webserver configurability, logging controls, and overall system robustness. His background from the University of Waterloo and early game and internship roles reflect a blend of strong CS fundamentals and hands-on production engineering. Colleagues rely on him for bridging research-quality models into reliable, observable services that operate at internet scale.
12 years of coding experience
7 years of employment as a software developer
BCS, Computer Science, BCS, Computer Science at University of Waterloo
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end & DevOps Engineer
Contributions:79 PRs, 25 pushes, 10 branches in 4 years 4 months
Contributions summary:Dan contributed to documentation, webserver configuration, and codebase improvements. They made the webserver worker timeout configurable and implemented features to control logging behavior. The user also addressed a variety of other issues related to user interface and system operations such as code quality and removing depreciated code. These commits demonstrate a broad understanding of the project's architecture and operational aspects.
Contributions:2 PRs, 436 pushes, 101 branches in 3 years 11 months
incubatingemrapachebig-dataspark
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Dan Davydov - Sr. Machine Learning Engineer at Twitter