At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github.About the RoleAs 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 GitHub, our forums, and Slack.About YouYou have a public track record of open-source work, and you enjoy collaborating with a community out in the open on GitHub. 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.What you'll needStrong Python skills, with experience writing clean, well-tested, maintainable library codeDeep 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 librariesA public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHubSolid understanding of modern machine learning and deep learning, including transformer architecturesExperience 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 communityNice to haveExperience maintaining an open-source projectPrior contributions to Transformers, Datasets, Accelerate, or similar librariesFamiliarity with distributed training, inference optimization, or GPU/accelerator performance workExperience training or fine-tuning models at scaleA note on fitIf 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.One more thingAt Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “GPU-poor and proud 🤗”. No trick, no catch, it just tells us a real person is on the other side. More about Hugging FaceWe 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.RequirementsPlease provide a cover letter mentioning why you would like to work in open-source at Hugging Face. We encourage you to mention your skills, potential expertise, and topics on which you would like to work.
At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github.
About the Role
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 GitHub, our forums, and Slack.
About You
You have a public track record of open-source work, and you enjoy collaborating with a community out in the open on GitHub. 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.
What you'll need
- 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
A note on fit
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.
One more thing
At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “GPU-poor and proud 🤗”. No trick, no catch, it just tells us a real person is on the other side.
More about Hugging Face
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.
Requirements
Please provide a cover letter mentioning why you would like to work in open-source at Hugging Face. We encourage you to mention your skills, potential expertise, and topics on which you would like to work.
Here at Hugging Face, we're on a journey to advance and democratize machine learning for everyone. Along the way, we contribute to the development of technology for the better. Over five thousand companies are using our technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.
