Hugging Face is hiring a Machine Learning Advocate Lead - International Remote

Description

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 technology development for the better.

We have built a platform in which over 100,000 models and thousands of demos and datasets are shared. From Computer Vision to Natural Language Processing and Audio, lots of communities are collaborating through the Hugging Face Hub to do open-source Machine Learning.

About the Role

As a Machine Learning Advocate Lead, 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 different domains and verticals (Computer Vision, Biotechnology, Healthcare, Art, 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 teams.

As an experienced engineer and advocate, you will be crucial in mentoring other team members, co-leading the roadmap to achieve growing usage by 100x, and having a multiplier effort in the Developer Advocacy and other teams. 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 to expand the Hub to new domains such as Reinforcement Learning or Computer Vision one week, and then craft blog posts, videos, talks, and demos the next one.

You'll get to foster machine learning communities, helping users contribute to and use the tools you build. You'll interact with Researchers, ML practitioners, and data scientists daily 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 with ML, have a solid understanding of the state of the field and ecosystem, and have an impact-driven mindset. If you want to contribute to making 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 backgrounds 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 you 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, as well as the future of machine learning more broadly. Hugging Face is an equal opportunity employer, and we do not discriminate based on race, ethnicity, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or ability 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 grow continuously. 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 offer health, dental, and vision benefits for employees and their dependents. 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.