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 over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.
About the Role
As an open-source machine learning engineer intern, you will work on skops (https://github.com/skops-dev/skops/) and its immediate surrounding ecosystem. skops sits on the edge of scikit-learn, mlops, and the Hugging Face Hub, and deals with challenges ranging from model serving, to model persistence, and model interpretation and model card generation. As an intern, you'd be working on one or more of these areas to move them further ahead while learning to deal with CI (continuous integration) and documentation builds. We will be mentoring you along the way and will give you clear tasks with clear expectations.
Some topics which you might deal with during the internship include:
Since you’ll focus on a subset of the above areas during the intership, you don’t need to be familiar with all the above topics to apply!
In this project, you will be mostly working with Python in the context of library development. It would help if you’re comfortable with your IDE, working with Python environments, and working in Python files instead of Python notebooks. Knowing object-oriented programming in Python would be a great advantage as well. For our unit tests, we use pytest.
Development happens on GitHub, therefore it’d be useful for you to know how git and GitHub work, be familiar with git based development workflow, as well as issues and pull requests on GitHub.
We have a strong focus on documentation and being able to communicate our work with others. Therefore your communication skills both in the context of work and in the context of code, are important to us.
How we work
Hugging Face is a distributed company and our team communicates mostly on GitHub and Slack. However, for the purpose of the internship for us it’s important that you have access to your mentors both physically and virtually. We’d like to work closely with you to make sure you have all you need to succeed at your internship. This means regular communication, both in person and online. We are very flexible on when these in-person visits happen and we’ll work on a schedule which would work for you based on your needs and constraints.
If you love open-source, are passionate about making complex technology more accessible, and want to contribute to one of the fastest-growing ML ecosystems, 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.
Ideally, you are based in Berlin, but we are open to remote work for the right candidate.
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 major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.