Edward Zeng is a cloud-focused software engineer and systems programmer based in Berkeley with six years of experience building and operating scalable infrastructure for AI workloads. He contributed to SkyPilot, an influential open-source project that unifies execution across Kubernetes and a dozen+ clouds, adding interactive node features, multi-cloud region/zone support, and Lambda Labs integration to improve usability and cost-efficient GPU access. A UC Berkeley-trained systems educator, he has taught and led CS162 (Operating Systems) as instructor and head TA, blending pedagogical clarity with deep systems knowledge. Edward holds dual BAs in Math and CS and an MS in EECS from Berkeley, and is pursuing a PhD in Mathematics at NYU Courant, reflecting strong mathematical rigor paired with practical engineering. His work sits at the intersection of devops, cloud engineering, and systems programming, with a penchant for making complex distributed tooling more accessible. His personal site and GitHub showcase a mix of research-minded problem solving and hands-on contributions that streamline real-world ML infrastructure.
6 years of coding experience
MS in Electrical Engineering and Computer Science, MS in Electrical Engineering and Computer Science at University of California, Berkeley
PhD in Mathematics (Expected), PhD in Mathematics (Expected) at Courant Institute of Mathematical Sciences
SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 16+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.
Role in this project:
Cloud Engineer / DevOps Engineer
Contributions:211 reviews, 5 commits, 24 PRs in 2 months
Contributions summary:Edward primarily contributed to the infrastructure and operational aspects of the SkyPilot project. Their work included modifying the `sky/cli.py` file to add features for interactive nodes, such as `--retry-until-up`, `--region`, `--zone`, and `--idle-minutes-to-autostop`. Further contributions involved fixing imports, modifying file permissions, and integrating support for the Lambda Labs cloud provider. These changes suggest a focus on enhancing usability and expanding the platform's compatibility.
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