At Hugging Face, we’re on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 5 million users & 100k organizations who collectively shared over 1M models, 300k datasets & 300k apps. Our open-source libraries have more than 400k+ stars on Github.
About the Role
In the past year the focus of building LLMs has gradually shifted from pretraining to post-training. This means spending more and more time on figuring out how to get models follow instructions reliably, use tools and generally align with certain values. With over 10k Github stars and close to 1M monthly installs the TRL library has become one of the go-to libraries for post-training. It scales flexibly from a single GPU to large clusters of GPUs using PEFT and ZeRO and offers a wide range of trainers for the latest post training techniques such as PPO or DPO and many more. In addition it includes a user friendly CLI that allows training models with a single command.
During this internship, you will collaborate with the research team to integrate cutting-edge methods into the library, maintain a clean and scalable codebase, and ensure its usability through thoughtful documentation. You’ll actively engage with the TRL community by responding to issues, gathering feedback, and fostering collaboration through thoughtful discussions and support, ensuring the library continues to meet developers' needs. Your contributions will directly influence thousands of developers globally, advancing the adoption of state-of-the-art post-training techniques and laying the groundwork for the next generation of customizable, instruction-following LLMs.
About You
We are looking for someone with knowledge and experience in some of the following areas:
You’re passionate about open-source innovation and making advanced ML tools accessible globally. You value continuity in software development, ensuring users have a dependable and evolving library to rely on.
Even if you don’t check every box, we encourage you to apply—we value diverse skills, perspectives, and experiences that complement our mission.
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 support our employees wherever they are. While we have office spaces around the world, especially in the US, Canada, and Europe, 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 support the community. We believe significant scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.
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.
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Are you ready to kickstart your career in artificial intelligence? Join Hugging Face as a Machine Learning Engineer Intern and become part of our exciting mission to democratize good AI! We’re building the fastest-growing platform for AI builders, attracting over 5 million users and 100,000 organizations, all sharing resources like models and datasets like never before. As an intern, you'll dive into the world of post-training techniques, collaborating with our research team to enhance our renowned TRL library. Imagine contributing to a tool that helps developers create customizable LLMs while engaging with the vibrant community around it. Your role will involve integrating state-of-the-art methodologies into the library, ensuring it's not only robust but also user-friendly through smart documentation and community engagement. You'll be fine-tuning models, coding with Python and PyTorch, and even sharing your insights through tutorials and blog posts to make complex ideas accessible. We value your unique perspective and experience, whatever your background may be, as long as you’re passionate about open-source innovation and ML tools. Not to mention, working remotely gives you the freedom to balance work and life, and we support you with resources for success. Come join us at Hugging Face, where your work will have a meaningful impact on the global developer community!
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