Juan Acevedo
Staff Machine Learning Engineer at Google
Irvine, California, United States
Summary
👤
Senior🎓
Top SchoolJuan Acevedo is a Staff Machine Learning Engineer based in Irvine with a decade of experience building and optimizing large-scale ML systems, now focused on Stable Diffusion research and engineering. At Google he progressed through roles in enterprise AI/ML infrastructure to staff-level contributions, blending production-ready systems expertise with model-level optimizations. He’s an active open-source contributor to high-profile projects like Hugging Face Diffusers, where he implemented Flax/JAX support, negative prompts, and XLA/PXLA performance improvements for Stable Diffusion pipelines. Comfortable across TPUs, GPUs, PyTorch and JAX, he brings a rare combination of low-level performance tuning and applied ML productization. His background in control systems and robotics informs a systems-minded approach to model robustness and scalable training pipelines.
10 years of coding experience
13 years of employment as a software developer
Cal Poly Pomona
Spanish, Japanese
Stackoverflow
1,788reputation
181kreached
37answers
20questions
Github Skills (19)
pytorch10
stable-diffusion10
flax10
jax10
text2image9
machine-learning9
deeplearning-ai9
image-generation9
deep-learning9
xla9
traffic6
wifi6
android6
tensorflow6
python6
Programming languages (7)
Github contributions (5)
huggingface/diffusers
Nov 2022 - Nov 2022
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 1 commit, 13 PRs in 1 day
Contributions summary:Juan primarily contributed to the integration and optimization of the Flax-based Stable Diffusion pipeline within the Diffusers library. Their work involved adding support for negative prompts in the Jax pipeline, implementing features related to splitting the head dimension in Flax attention, and enabling PXLA training for Stable Diffusion 2.x models. They also worked on XLA integration and performance improvements for the training and inference pipelines.
pytorchartdeep-learningimage2imagestate-of-the-art
entrpn/diffusers
Nov 2022 - Mar 2025
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
Contributions:80 pushes, 19 branches in 2 years 4 months
pytorchartdeep-learningstate-of-the-arttext-to-image
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