Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.
We have built the fastest-growing, open-source, library of pre-trained models in the world. With more than 500K+ models and 250K+ stars on GitHub, over 15.000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.
About the Role
Post-training is an exciting and fast-moving field of research that is used to enhance the performance of large language models and enable them to follow human instructions. The post-training team at Hugging Face is pushing the frontier of model capabilities by developing recipes [1] that produce state-of-the-art models like Zephyr [2] and NuminaMath [3], which won the 1st Progress Prize of the AI Math Olympiad.
During this internship, you will work alongside the post-training team to implement cutting-edge research and make it accessible to the global AI community in the form of code, datasets, and models. Topics include training LLMs how to reason via test-time compute and how to navigate complex environments that require agentic behaviour. You will have access to a state-of-the-art training codebase, a large research cluster of H100s, and domain experts in Hugging Face's science team.
If you enjoy training LLMs and working across the whole deep learning stack, we’d love to hear from you!
Check out hf.co/science for more information about the science team at Hugging Face and https://huggingface.co/HuggingFaceH4 for more information on our post-training projects.
[1] Alignment Handbook - robust recipes for post-training https://github.com/huggingface/alignment-handbook
[2] Zephyr https://huggingface.co/HuggingFaceH4/zephyr-7b-beta
[3] NuminaMath https://huggingface.co/blog/winning-aimo-progress-prize
About You
If you love open-source but also have an eye for art and creativity, are passionate about making complex technology more accessible to engineers and artists, and want to contribute to one of the fastest-growing ML ecosystems, then we can't wait to see your application!
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 background complement one another. We're happy to consider where you might be able to make the biggest impact.
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.
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.