James Betker
Research Engineer at Garmin International
Boulder, Colorado, United States
Summary
🤩
Rockstar🎓
Top SchoolJames Betker is a research engineer with 15 years of experience building production-grade software and generative models for images and audio, currently developing cutting-edge generative systems at OpenAI from Boulder, Colorado. His background spans embedded and automotive systems at Garmin—where he led multimedia and navigation software efforts and ported platforms to Android—and security-oriented engineering at Google, showing a rare blend of low-level system design and ML research. Active on GitHub as a "Latent Analyst, Entropy Wrangler," he has hands-on contributions to high-quality TTS work, specifically advancing a discrete diffusion vocoder in the popular tortoise-tts project. He pairs strong C/C++ and embedded systems pedigree with modern ML model engineering, making him effective at bridging research prototypes into robust product components.
14 years of coding experience
10 years of employment as a software developer
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at UC Santa BarbaraBS, Computer Science, BS, Computer Science at University of California, Santa Barbara
Stackoverflow
61reputation
2kreached
0answers
3questions
Github Skills (11)
diffusion-models10
pytorch10
machine-learning10
audio-processing10
deep-learning10
python10
transformer-models6
huggingface-transformers6
keras6
nlp6
tensorflow6
Programming languages (5)
Github contributions (5)
neonbjb/tortoise-tts
Jan 2022 - Jan 2023
A multi-voice TTS system trained with an emphasis on quality
Role in this project:
ML Engineer
ML EngineerContributions:12 reviews, 168 commits, 32 PRs in 1 year
Contributions summary:James's commits focus on the development and modification of a discrete diffusion vocoder model within the tortoise-tts project, suggesting a focus on audio generation. Their work involves implementing and modifying residual blocks, attention mechanisms, and timestep embeddings, indicating expertise in the core architecture of the diffusion model. The commits demonstrate the user's direct involvement in adjusting the model to work with a spectrogram prior, which helps with improving audio quality.
pytorchvoicequalityemphasistts
neonbjb/ocotillo
Nov 2021 - May 2022
Performant and accurate speech recognition built on Pytorch
Contributions:3 releases, 48 commits, 25 pushes in 6 months
pytorchspeech-to-textrecognitionctcspeech-recognition
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