Source Machine Learning Engineer - US Remote

At Hugging Face, we're on a journey to democratize good AI. We're building the fastest-growing platform for AI builders, with over 11 million users who have shared more than 2M models, 700k datasets, and 600k apps. Our open-source libraries have more than 600k stars on Git Hub.

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 Git Hub, our forums, and Slack.

You have a public track record of open-source work, and you enjoy collaborating with a community out in the open on Git Hub. 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.

• 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 Tensor Flow 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 Git Hub
• Solid understanding of modern machine learning and deep learning, including transformer architectures
• Experience collaborating with a technical community in the open (Git Hub 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

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.

We are actively working to build a culture that values diversity, equity, and inclusivity
. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.

We care about your well‑being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.

We support our employees wherever they are
. While we have office spaces in NYC and Paris, we’re very distributed and all remote employees have the opportunity to visit our offices. If needed, we’ll also outfit your workstation to ensure you succeed.

We want our teammates to be shareholders
. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.

We support the community
. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.