Clay Mullis
Software Developer at Walmart
Fayetteville, Arkansas, United States
Summary
🤩
Rockstar🎓
Top SchoolClay Mullis is a software developer with 10 years of experience building data-driven web applications, currently engineering React and Django solutions at Walmart from Fayetteville, Arkansas. He blends practical full-stack web development with a strong computer science foundation from the University of Arkansas and early exposure to security and enterprise-grade systems. Clay contributes to notable open-source ML work—improving training stability and mixed-precision support for a PyTorch replication of OpenAI’s DALL·E—demonstrating both ML engineering chops and attention to performance/VRAM optimization. Comfortable across stacks (C#, Java, Python, React/Django), he brings a pragmatic, security-aware mindset and a track record of shipping reliable, production-ready software.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at University of Arkansas at FayettevilleHigh, High at Fayetteville High School
English
Github Skills (10)
attention-mechanism10
transformers10
pytorch10
machine-learning10
artificial-intelligence10
deep-learning10
trainings10
python10
modeling10
multiprecision9
Programming languages (16)
Github contributions (5)
lucidrains/DALLE-pytorch
Mar 2021 - Sep 2021
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Role in this project:
ML Engineer
ML EngineerContributions:36 reviews, 33 commits, 58 PRs in 6 months
Contributions summary:Clay focused on improving the training process and stability of the DALL-E model. Their contributions included fixing issues related to resuming training, optimizing VRAM usage, and incorporating mixed-precision training (Apex O1). Furthermore, the user added features like gradient accumulation and exposed parameters for the flops profiler, improving the model's training and analysis capabilities. They also made changes to the dataset and tokenizer to improve stability during training.
pytorchmulti-modaltransformersdall-eattention-mechanism
afiaka87/laionide
Feb 2022 - Aug 2022
checkpoints for glide finetuned on laion and other datasets. wip.
Contributions:17 commits, 16 pushes, 1 branch in 6 months
wipdatasetdatasetspiiglide
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