Michael Wilson is a Senior Data Scientist with 16 years of experience building production ML systems that bridge research-grade modeling and reliable, scalable deployment. He has led ML efforts at Zoox and Dropbox—delivering revenue-driving propensity and recommendation models, accelerating model deployment pipelines, and improving computer-vision model precision for robotaxi perception. Comfortable from C++ scientific toolkits to Spark and Java microservices, he pairs deep statistical rigor with pragmatic engineering: instrumentation, monitoring, and on-call runbooks are as familiar to him as training-data curation and dataset optimization. He’s contributed backend enhancements to the widely used Teleport project, demonstrating an ongoing commitment to secure, auditable infrastructure. Based in California with a PhD in physics, he excels at translating complex, messy data into measurable product value while mentoring teams and shaping robust ML workflows.
The easiest, and most secure way to access and protect all of your infrastructure.
Role in this project:
Back-end Developer
Contributions:1189 reviews, 240 commits, 1274 PRs in 4 months
Contributions summary:Michael's contributions primarily focused on implementing and refining audit events, along with changes to application login via `tsh app login`. The user added new application CRUD audit events and integrated them in the frontend. They modified the service's gRPC code to capture additional application details, and removed an unused header from the application server.
A multitrack player that runs on Linux and outputs to class compliant devices.
Contributions:2 releases, 6 reviews, 125 PRs in 11 months
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