Tanner Davis is a Senior Machine Learning Engineer with nine years of experience building production-grade deep learning systems, particularly at the intersection of healthcare, biotech, and operational industries. He architects scalable, distributed ML platforms—recently delivering a lab automation stack with AWS Step Functions and 200%+ inference improvements via GPU optimizations and dynamic batching. His work spans multimodal search and geospatial vision for asset identification, intelligent document processing, and whole-slide image segmentation for faster cancer diagnosis, showing both domain breadth and production rigor. Based in Salt Lake City, he champions automation and reproducible deployments through reusable GitHub Actions while keeping a sharp focus on compliance for PHI/HIPAA-sensitive workflows. Notably, Tanner blends hands-on model optimization with infrastructure engineering, making research-ready models reliably deployable across multiple research teams.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS Computer Science - Data Science Emphasis, Bachelor of Science - BS Computer Science - Data Science Emphasis at Brigham Young University
A Dart/Flutter wrapper around the current Stripe API
Contributions:22 commits, 5 PRs, 14 pushes in 7 days
apistripedart2dartstripe-api
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