Internship for Machine Learning Engineer at Brrr/Nanotron - Remote in EMEA

Here at Hugging Face, we're on a journey to enhance beneficial Machine Learning and make it more accessible. As we progress, we contribute to the advancement of technology for the better.

We've built the fastest-growing, open-source library of pre-trained models worldwide. With over 500K+ models and 250K+ stars on GitHub, more than 15,000 companies are utilizing HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.

About the Role

Hugging Face employs a specific 3D parallelism distributed training library internally to train its LLM (which we plan to open-source eventually). You will join the small team that maintains and enhances this library. You should enjoy diving into CUDA kernels and performance optimization.

About You

If you adore open-source, are passionate about making intricate technology more accessible to engineers and artists, and want to contribute to one of the fastest-growing ML ecosystems, we can't wait to receive your application!

Even if you don't meet every criterion above, we still encourage you to apply! We're assembling a diverse team whose skills, experiences, and backgrounds complement each other. We're eager to explore where you could make the most significant impact.

More about Hugging Face

We're actively striving to cultivate a culture that values diversity, equity, and inclusivity. We are purposefully constructing a workplace where individuals feel respected and supported—regardless of who they are or where they come from. We believe this is a fundamental element in creating an excellent company and community. Hugging Face is an equal opportunity employer, and we don't discriminate on attributes such as race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We value growth. You will work alongside some of the preeminent figures in our industry. We are an organization with a bias for impact that consistently challenges ourselves to continuously develop. We provide all employees with compensation for relevant conferences, training, and education.

We care for your welfare. We offer flexible work hours and remote alternatives. We support our employees wherever they are. Although we have office spaces worldwide, 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 equip your workstation to ensure you succeed.

We back the community. We acknowledge that significant scientific advancements result from collaboration within the field. Join a community that supports the ML/AI community.