Douglas Reeves
Machine Learning Engineer
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolDouglas Reeves is a Machine Learning Engineer and Data Scientist based in San Francisco with eight years of hands-on experience across ML, application development, information security, and network engineering. He blends deep learning expertise with practical production skills, often approaching problems from both a data-driven and security-conscious perspective. Trained at Galvanize in SoMa, he has a Bay Area tech mindset and an ongoing fascination with how AI reshapes creative domains. Outside core engineering, Douglas brings a rare combination of music production and audio engineering knowledge that informs his work on ML for audio and signal processing. Colleagues value his ability to translate research ideas into deployable systems while keeping operational reliability and security front of mind. He’s driven by curiosity about the future of AI and how it intersects with creative workflows.
8 years of coding experience
Galvanize - San Francisco, SoMa
Github Skills (5)
generative4
generative-adversarial-network3
source-separation2
deep-learning2
pytorch2
Github contributions (5)
NullspaceSF/DSSGAN
Jul 2018 - Aug 2018
Drum Source Separation via Generative Adversarial Network
Contributions:32 commits, 2 PRs, 26 pushes in 29 days
pytorchsource-separationdeep-learningadversarialdrum
NullspaceSF/AAS
Jul 2018 - Aug 2018
Contributions:62 pushes, 2 branches in 24 days
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