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.
Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are always looking to push the boundaries for faster, and more efficient ways to train and deploy models.
About the Role
If you are passionate about building Machine Learning solutions used by millions leveraging the cloud stack and services of Cloud Service Providers: we should talk!
We are looking for talented people with deep experience and passion for both Machine Learning (at the framework level) and Cloud Services:
- Bridging & Integrating 🤗 transformers/diffusers models with a different Cloud provider.
- Ensuring the above models meet the expected performance
- Designing & Developing easy-to-use, secure, and robust Developer Experiences & APIs for our users.
- Sharing & Advocating your work and the results with the community.
This is an exciting opportunity to work at the edge of state-of-the-Art Machine learning and Cloud development. As additional material, you may want to take a look at the announcements on our The Partnership: Amazon SageMaker and Hugging Face or Hugging Face Collaborates with Microsoft to Launch Hugging Face Endpoints on Azure to get a better sense of what it means in practice 🤗.
About You
You'll enjoy working in this team if you like putting things into production and creating services, which let users to benefit from your work and knowledge about Cloud providers, MLOps, software engineering, and machine learning. At the intersection of software engineering and machine learning, you would be in charge of integrating the latest features from our open-source libraries in Python/Rust, designing rich and easy Python & Web APIs in the continuity of what Hugging Face did with AWS and Azure with a strong focus on adoption and enablement. Frontend engineering and Business knowledge would be a great plus for the job.
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 offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave 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.
