Here at Hugging Face, we’re on a journey to advance and democratize Machine Learning for everyone. We create techniques that enable people to develop ML regardless of their background. We contribute to the development of technology informed not only by science but also by society and people. To this end, we have built open-source machine learning libraries, tools, and platforms that have been downloaded over 100 million times and powered tech production in thousands of companies.

About the Role

As a Machine Learning Engineer in the Developer Advocacy Team, you will have a key role in driving the adoption of the Hugging Face Hub platform and Open Source technologies by contributing to the OS ecosystem in the Healthcare and Medical industry (NLP, Computer Vision, etc), crafting tools to improve developer experience, and extending the use cases of the Hub. You’ll collaborate closely with Open Source, Research, and Product, and especially with the ecosystem in the domain.

As an experienced engineer in the ecosystem, you will take a leading role in defining and executing a roadmap, in enabling the Healthcare and Medical communities to collaborate with Hugging Face Open Source tools and the Hub. It’s important to us that each team member works on interesting and impactful projects. Depending on your interests, you could work on developing tools for the Healthcare sector one week, add datasets for medical imaging the next week, and craft blog posts, videos, talks, and demos the one after that!

Our community contributors have released work in this space from training NER models for electronic health records and building demos of GANs to generate cornea scans with a variety of pathologies, to sharing models for robotic-assisted surgery.

You'll get to foster machine learning communities, helping users contribute to and use the tools that you build. You'll interact with Researchers, ML practitioners and data scientists on a daily basis through GitHub, our forums, or Discord.

About you

You'll love working here if you love Open Source and would like to amplify your impact by engaging with the ecosystem. We’re looking for candidates who have experience training ML models, analyzing and constructing datasets, and have a solid understanding of the state of the Healthcare/Medical ecosystem. If you want to contribute to taking one of the fastest-growing ML companies to the next level, 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 as well as unlimited PTO. We offer health, dental, and vision benefits for employees and their dependents and a monthly fitness reimbursement to support your physical health. We also offer 12 weeks of parental leave (20 for birthing mothers) and unlimited paid time off.

We support our employees wherever they are. While we have office spaces in NYC and Paris, 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 want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.

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.