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18 Best PyTorch Developers

pytorch developers - 18 Best PyTorch Developers

PyTorch has become one of the most widely adopted deep learning frameworks in the world, driven by a diverse and passionate global community.

This includes prolific open-source contributors, startup founders still writing code, renowned educators and content creators, engineers building at scale inside major tech companies, and even winners of international AI competitions. Below is an updated and ranked list of 18 of the world’s best PyTorch developers, selected for their influence, activity, and contributions across these areas:

  1. Dmytro Dzhulgakov
  2. Phillip Lippe
  3. Shauheen Zahirazami
  4. Thomas Wolf
  5. Lysandre Debut
  6. Jeremy Howard
  7. William Falcon
  8. Tim Dettmers
  9. Sebastian Raschka
  10. Sylvain Gugger
  11. Thomas Viehmann
  12. Luca Antiga
  13. Yacine Jernite
  14. Seth Juarez
  15. Jason Brownlee
  16. Rachel Thomas
  17. Steve Wan
  18. Niles Burbank

Now, let’s delve deeper into each of these developers’ accomplishments and contributions:

Dmytro Dzhulgakov

YouTube Video

Nationality: Ukrainian

Dmytro Dzhulgakov is a technical lead for the PyTorch framework at Meta AI.

With five years on the PyTorch team, he focuses on core development and production deployment of PyTorch. He also co-created ONNX (the open neural network interoperability format) and has worked on scaling Facebook recommendation systems using PyTorch. His role ensures PyTorch’s stability and performance in large-scale systems, making him a key figure in the PyTorch open-source community.

Phillip Lippe

Nationality: German

Phillip Lippe is a research scientist at Google DeepMind and an educator in the PyTorch Lightning community.

He co-developed the University of Amsterdam’s deep learning tutorials, which were later integrated as official tutorials in PyTorch Lightning’s documentation. Lippe’s work bridges academia and PyTorch: by using and teaching PyTorch Lightning in coursework, he has helped train many students and made advanced PyTorch features more accessible to learners.

Shauheen Zahirazami

Accelerating PyTorch workloads on Cloud TPU with Pallas integration and Auto-Sharding.

Nationality: Iranian-American

Shauheen Zahirazami is a Google engineer who leads Cloud TPU Machine Learning Teams (ML Frameworks).

His team develops PyTorch/XLA, the backend that enables PyTorch to run on Google’s TPUs. By contributing PyTorch support for TPUs, Shauheen has opened up PyTorch to a wider range of high-performance hardware. His work on PyTorch/XLA is critical for researchers who want to train PyTorch models on Google Cloud’s specialized accelerators.

Thomas Wolf

Thomas Wolf 1 - 18 Best PyTorch Developers

Nationality: French

Thomas Wolf is co-founder and Chief Science Officer of Hugging Face, an AI company known for NLP tools.

He led development of the popular Transformers and Datasets libraries (both built on PyTorch), democratizing access to state-of-the-art NLP models. Wolf actively promotes open-source and education: he co-authored Natural Language Processing with Transformers and organizes research projects like BigScience for large language models. Under his leadership Hugging Face has become a major hub of PyTorch-based models and community, reflecting his huge influence on the PyTorch ecosystem.

Lysandre Debut

Nationality: French

Lysandre Debut is Head of Open Source at Hugging Face and a core maintainer of the Transformers library.

He has been at Hugging Face since its pivot to open source and helped launch its mission. In late 2023 he led Hugging Face’s integration with the PyTorch Foundation, emphasizing interoperability. Lysandre’s contributions lie in keeping Hugging Face’s PyTorch tools (Transformers, tokenizers, etc.) cutting-edge and well-supported, cementing the link between PyTorch and Hugging Face’s ecosystem.

Jeremy Howard

Nationality: Australian

Jeremy Howard is a data scientist and educator who co-founded the fast.ai deep learning group.

He co-authored Deep Learning for Coders with fastai and PyTorch, and his fastai library (built on PyTorch) is widely used for teaching and research. A former Kaggle Grandmaster and founding CEO of Kaggle, he has used competitions and education to popularize practical deep learning. Howard’s work emphasizes making AI accessible; through fast.ai courses and libraries he has taught tens of thousands of developers to use PyTorch for vision and NLP tasks.

William Falcon

William Falcon 1 - 18 Best PyTorch Developers

Nationality: Cuban-American

William Falcon is the creator of PyTorch Lightning and CEO of Lightning AI.

PyTorch Lightning is a high-level framework that simplifies PyTorch training loops for distributed GPUs/TPUs. Falcon has a background as an AI researcher (PhD-level) and has built developer tools like Lightning and TorchMetrics to make PyTorch more usable. His efforts (such as Lightning’s open-source code) emphasize best practices and research productivity, making him a prominent developer in the PyTorch community.

Tim Dettmers

Nationality: German

Tim Dettmers is a research scientist at the Allen Institute for AI (AI2) and incoming assistant professor at Carnegie Mellon.

He is known for his influential blog on efficient deep learning (e.g. model quantization), and created the bitsandbytes library for 8-bit model training in PyTorch. His work makes large neural networks more accessible (e.g. 8-bit optimizers for LLMs), bridging research and practical PyTorch tools. Dettmers’s clear tutorials and code have guided many engineers in optimizing PyTorch models at scale.

Sebastian Raschka

Sebastian Raschka - 18 Best PyTorch Developers

Nationality: German

Sebastian Raschka is an associate professor at UW–Madison and a prolific ML author.

He wrote Python Machine Learning and Machine Learning with PyTorch & Scikit-Learn, and developed many PyTorch-based educational examples. Notably, he transitioned his deep learning coursework from TensorFlow to PyTorch around 2016, championing PyTorch’s simplicity. Raschka’s extensive tutorials and books help newcomers learn PyTorch for computer vision and NLP, and his GitHub repos contain dozens of PyTorch demos. His teaching and writing have made him a leading influencer in the PyTorch community.

Sylvain Gugger

Nationality: French

Sylvain Gugger is a former Hugging Face engineer and co-author of the fast.ai deep learning book (with Jeremy Howard).

He helped integrate PyTorch into fastai and worked on Hugging Face’s model libraries. Currently at Jane Street, Gugger continues to publish PyTorch-focused tutorials and notebooks to educate the community. His contributions lie in making PyTorch-based deep learning more approachable, through clear teaching materials and tool development.

Thomas Viehmann

Nationality: German

Thomas Viehmann is a machine learning engineer and PyTorch core developer.

He co-wrote Deep Learning with PyTorch and offers training and consulting on PyTorch. As a contributor to PyTorch’s codebase and documentation, Viehmann helps improve PyTorch’s functionality and usability. He maintains popular PyTorch example repositories and has given talks/workshops on PyTorch, making him a respected expert in the framework.

Luca Antiga

Luca Antiga - 18 Best PyTorch Developers

Nationality: Italian

Luca Antiga is CTO at Lightning AI and an early contributor to PyTorch’s core code.

He co-authored Deep Learning with PyTorch and led engineering on deploying PyTorch models. Luca’s work bridges research and production – he co-founded ONNX for model interoperability and focuses on deploying AI in production settings. As a PyTorch contributor and Lightning leader, he has significantly influenced how PyTorch models are used at scale.

Yacine Jernite

Nationality: Belgian

Yacine Jernite is the ML & Society lead at Hugging Face and a co-organizer of the BigScience project.

He coordinated the large language model BLOOM development, which uses PyTorch for training. Jernite’s expertise in data and model governance helped structure Hugging Face’s open research. He continues to contribute to Hugging Face’s PyTorch-based toolchain and leads initiatives (e.g. BigScience, BigCode) to build and analyze large models in a collaborative way.

Seth Juarez

Seth Juarez - 18 Best PyTorch Developers

Nationality: American

Seth Juarez is a data scientist and educator, formerly at Microsoft, known for co-authoring Microsoft’s PyTorch Fundamentals course.

He teaches PyTorch concepts through blog posts, videos, and the Machine Learning Street Talk podcast. Juarez’s approachable style and open tutorials (often on Twitter/X and his blog) have made complex PyTorch topics accessible. He continues to code and present PyTorch demos in talks, making him an influential community educator.

Jason Brownlee

Nationality: Australian

Jason Brownlee, PhD is a machine learning educator and founder of MachineLearningMastery.com.

He publishes many practical tutorials on PyTorch (e.g. step-by-step guides and mini-courses) to help developers get hands-on with deep learning. His blog posts and ebooks cover PyTorch fundamentals, and his “Deep Learning Crash-Course” uses PyTorch examples. Brownlee’s educational content is widely used by practitioners and students learning PyTorch.

Rachel Thomas

Rachel Thomas - 18 Best PyTorch Developers

Nationality: American

Rachel Thomas is co-founder of fast.ai and Professor of Practice at the University of San Francisco.

She co-created the world’s longest-running free deep learning course (fast.ai) and co-authored chapters in Deep Learning for Coders with fastai and PyTorch. Her work has focused on making deep learning (especially NLP) accessible, teaching many students through fast.ai’s PyTorch-based courses. Thomas is also noted for her advocacy on ethics in AI and for integrating PyTorch hands-on labs in education.

Steve Wan

Nationality: American

Steve Wan is an engineering manager at Microsoft Azure responsible for the AI-at-Scale initiative.

A key part of his role is “enabling and innovating on PyTorch” for Azure’s cloud AI platform. He works on integrating PyTorch into Azure Machine Learning and optimizing it for scalable deployment. Wan’s efforts ensure that developers can efficiently train and deploy PyTorch models on Microsoft’s large-scale cloud infrastructure.

Niles Burbank

Nationality: Canadian

Niles Burbank is Director of Product Management for Data Center GPUs at AMD.

He oversees AMD’s GPU lineup and works to advance software for AI. While not a core PyTorch developer, his role in promoting open-source ML tools (including support for PyTorch on AMD hardware) has helped expand PyTorch’s reach. Burbank collaborates with the AI community to deliver tools and drivers that enable PyTorch to run efficiently on AMD GPUs.

Wrap Up

These legends represent exceptional talent, making them extremely challenging to headhunt. However, there are thousands of other highly skilled IT professionals available to hire with our help. Contact us, and we will be happy to discuss your hiring needs.

Note: We’ve dedicated significant time and effort to creating and verifying this curated list of top talent.
However, if you believe a correction or addition is needed, feel free to reach out. We’ll gladly review and update the page.

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