Description
As an Open-Source Machine Learning Engineer at Hugging Face, 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 interact with users and contributors across the broad open-source ML ecosystem.
You'll help foster one of the most active machine learning communities, assisting users in contributing to and using the tools you build. You'll collaborate with researchers, ML practitioners, and data scientists daily through GitHub, 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
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
Benefits:
- Reimbursement for relevant conferences, training, and education
- Flexible working hours and remote options
- Health, dental, and vision benefits for employees and their dependents
- Parental leave and flexible paid time off
- Company equity as part of the compensation package