[Hiring] Open-Source Machine Learning Engineer @Hugging Face

Role Description

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.

• Help foster one of the most active machine learning communities.
• Assist users in contributing to and using the tools you build.
• Collaborate with researchers, ML practitioners, and data scientists through GitHub, forums, and Slack.

Qualifications

• 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.

Requirements

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

Benefits

• Flexible working hours and remote options.
• Health, dental, and vision benefits for employees and their dependents.
• Parental leave and flexible paid time off.
• Reimbursement for relevant conferences, training, and education.
• Company equity as part of the compensation package.
• Support for remote employees to visit office spaces in NYC and Paris.
• Workstation outfitting to ensure success.