Open-Source Machine Learning Engineer - US Remote

Hugging Face is a company dedicated to democratizing AI and building a platform for AI builders. As an Open-Source Machine Learning Engineer, you will improve the open-source machine learning ecosystem by working on libraries such as Transformers and Datasets, and engaging with users and contributors across the community.

Responsibilities:

• Work to improve the open-source machine learning ecosystem
• Mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch and vLLM
• Interact with users and contributors across the broad open-source ML ecosystem
• Help foster one of the most active machine learning communities, helping users contribute to and use the tools you build
• Work with researchers, ML practitioners, and data scientists every day through GitHub, our forums, and Slack

Requirements:

• 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
• 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