Zach Evans is a technology leader with six years of focused experience in AI and a longer track record building user-facing software at Microsoft. As Head of Harmonai at Stability AI, he manages communities of researchers and creative artists advancing open-source generative media while contributing hands-on ML engineering work—most notably implementing audio diffusion components for a dance-focused generative audio project. His background includes senior UX and cloud-focused engineering at Microsoft and teaching roles that reflect strong communication and mentorship skills. Based in Issaquah, Washington, he blends product-minded engineering with research collaboration, comfortable moving between production web/UX systems and low-level ML model training pipelines.
6 years of coding experience
7 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Western Washington University
Tools to train a generative model on arbitrary audio samples
Role in this project:
ML Engineer
Contributions:2 reviews, 54 commits, 20 PRs in 8 months
Contributions summary:Zach implemented audio diffusion code, specifically integrating it into a finetuning script for a dance diffusion model. This involved defining noise schedules, sampling loops, and loss functions, all critical for training and generating audio samples. The changes indicate a focus on the core machine learning aspects of audio generation, likely for creating novel audio from an existing model.
Generative models for conditional audio generation
Contributions:7 reviews, 50 PRs, 67 pushes in 1 year 4 months
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