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 1 Million+ models and 320K+ stars on GitHub, over 15.000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly and NASA. About the Role To fulfill our mission of building the Github of Machine Learning, our team is now looking for a Product Engineer with experience working in a fast-paced environment. In this unique position, you will play a key role by building the essential tooling required to interact with our Machine Learning Hub, which is rapidly becoming a go-to destination for companies and individuals to host and run their models. You’ll work with a supportive team of talented engineers while enjoying a lot of autonomy to build and own features end-to-end. This is a great opportunity to be an early contributor to the biggest platform shift of the decade. About You You’ll enjoy working here if you are: Enthusiastic about working on technical challenges for ML-focused products. Are a generalist and polyglot engineer with an ability to pick up new frameworks quickly and willing to work across the stack from backend to frontend (Typescript, Node.js, Svelte, MongoDB, AWS). Comfortable working in a fast-paced and ambiguous environment, aka shifting sands of startup land. Excited to be a builder for builders! Empathy for developers across the stack and an enthusiasm for developer-first products. A great product sense and experience building products that our users rely on. Enjoy understanding technical domains deeply and are willing to really get into the weeds. A high sense of technical and product ownership and a desire to please the customer. You know what it takes to build cross-platform tools, and you have experience working collaboratively across the stack. 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 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 toward 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 flexible parental leave and 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.
TypeScript GitHub Backend Node.js Machine Learning Amazon Web Services (AWS) MongoDB Svelte Frontend