Open-Source Machine Learning Engineer (AI)

Location: Remote, based in New York, New York, United States

Company

Hugging Face builds an open-source platform and ecosystem for AI and machine-learning developers, including models, datasets, applications, and development libraries.

What you will do

• Improve open-source machine-learning libraries including Transformers, Datasets, PyTorch, and vLLM.
• Build clean, well-tested, and maintainable library code.
• Help users contribute to and use open-source machine-learning tools.
• Collaborate with researchers, ML practitioners, data scientists, users, and contributors through GitHub, forums, and Slack.
• Support the open-source machine-learning community and make complex technology more accessible.

Requirements

• Strong Python skills and experience writing tested library code.
• Hands-on experience with a modern deep-learning framework, especially PyTorch.
• Experience with the Hugging Face open-source stack or comparable machine-learning libraries.
• Public open-source contributions, such as merged pull requests to ML or data libraries.
• Understanding of modern machine learning, deep learning, and transformer architectures.
• Fluent written English required for asynchronous collaboration across a distributed community.

Nice to have

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

Culture & Benefits

• Flexible working hours and remote work options.
• Health, dental, and vision benefits for employees and dependents.
• Parental leave and flexible paid time off.
• Reimbursement for relevant conferences, training, and education.
• Company equity for all employees.
• Access to offices in New York City and Paris, with workstation equipment available when needed.

Hiring process

• Submit a cover letter explaining interest in open-source work at Hugging Face.
• Include relevant skills, expertise, and topics of interest for potential contribution.
• Start the first application-question answer with “GPU-poor and proud”.