About the Role

As an Open-Source Machine Learning Engineer, you'll work to improve the open-source machine learning ecosystem. You'll mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch and vLLM, and you'll interact with users and contributors across the broad open-source ML ecosystem. We'll brainstorm with you to put you in a position to do the work that interests you and that is impactful.

You'll help foster one of the most active machine learning communities, helping users contribute to and use the tools you build. You'll work with researchers, ML practitioners, and data scientists every day through GitHub, our forums, and Slack.
About You

You have a public track record of open-source work, and you enjoy collaborating with a community out in the open on GitHub. You love open source, you're passionate about making complex technology more accessible, and you want to contribute to one of the fastest-growing ML ecosystems. If that's you, we can't wait to see your application.
What you'll need

• Strong Python skills, with experience writing clean, well-tested, maintainable library code
• Deep hands-on experience with a modern deep-learning framework, especially PyTorch (JAX or TensorFlow a plus)
• Practical experience with the Hugging Face open-source stack (Transformers, Datasets, Accelerate) or comparable ML libraries
• A public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHub
• Solid understanding of modern machine learning and deep learning, including transformer architectures
• Experience collaborating with a technical community in the open (GitHub issues and reviews, forums, Slack or Discord)
• Fluent written English for asynchronous collaboration across a distributed, global community

Nice to have

• Experience maintaining an open-source project
• Prior contributions to Transformers, Datasets, Accelerate, or similar libraries
• Familiarity with distributed training, inference optimization, or GPU/accelerator performance work
• Experience training or fine-tuning models at scale

A note on fit

If you're interested in joining us but don't tick every box above, we still encourage you to apply. We're building a diverse team whose skills, experiences, and backgrounds complement one another, and we're happy to consider where you might make the biggest impact.
How to apply

At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we genuinely read every application, here's a small sign that you read this one too: start your cover letter with the words "GPU-poor and proud of it " so we know you read the full description. No trick, no catch, it just tells us a real person is on the other side.

Requirements

Please provide a cover letter mentioning why you would like to work in open-source at Hugging Face. We encourage you to mention your skills, potential expertise, and topics on which you would like to work.