Geoffrey Salisi is a software engineer based in San Francisco with 12 years of experience building scalable tools for autonomous vehicle platforms and cloud-native workloads. He has led frontend and backend efforts at Lyft and Woven by Toyota, creating data exploration and 3D visualization tools and operating petabyte-scale batch compute for simulation workloads. His work blends pragmatic frontend leadership—designing reusable components and streaming optimizations—with systems engineering: implementing scatter-gather deployment across EKS, improving spot-instance resilience, and instrumenting notebook-based observability. Currently at DoorDash, he continues to apply that full-stack mentality to production-grade services. Known for turning complex pipeline and visualization problems into practical, measurable improvements, he pairs strong implementation skills in Go and Python with a user-focused approach to tooling.
12 years of coding experience
7 years of employment as a software developer
Computer Engineering, Computer Engineering at University of Waterloo
Contributions:4 PRs, 75 pushes, 2 branches in 8 months
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