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 1M+ models and 400K+ 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 RoleIn 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 YouWe are looking for someone with knowledge and experience in some of the following areas: Machine Learning: Fine-tuning large language models (LLMs) or vision-language models (VLMs), and optimisation techniques.

Software Development: Proficiency in Python, PyTorch, and frameworks like Hugging Face Transformers, with experience in distributed training and GPU acceleration.

Open-Source: Familiarity with Git/GitHub workflows, community engagement, documentation, and collaborative development.

Research and Experimentation: Exposure to cutting-edge ML research, benchmarking, and testing fine-tuning methods.

Tooling and Maintenance: Building tools to streamline workflows, ensuring software stability, backward compatibility, versioning, and delivering reliable releases.

Communication and Outreach: Writing blog posts, tutorials, and sharing updates on platforms like LinkedIn to engage with the community and make complex concepts accessible to a wider audience.

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 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 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.