Join Hugging Face as a Cloud Machine Learning Engineer - EMEA Remote

At Hugging Face, we are on a mission to advance good Machine Learning and make it more accessible. Through our efforts, we contribute to the development of technology for the greater good.

About Hugging Face

We have built the world's fastest-growing, open-source library of pre-trained models. With more than 1 Million+ models and 320K+ stars on GitHub, our technology is utilized in production by over 15,000 companies, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly, and NASA.

Hugging Face has become the most popular community-driven project for training, sharing, and deploying advanced machine learning models. Efficiency is key to our mission of democratizing state-of-the-art technology, constantly pushing the boundaries for faster and more efficient model training and deployment.

About the Role

We're seeking a Cloud Machine Learning Engineer to build machine learning solutions utilized by millions leveraging cloud technologies. Your work will involve integrating Hugging Face's open-source libraries like Transformers and Diffusers with major cloud platforms or managed SaaS solutions.

Explore our collaborations like Hugging Face and AWS Partner to Make AI More Accessible, Hugging Face and IBM Partner on Watsonx.ai, Introducing SafeCoder, or Hugging Face Collaborates with Microsoft to launch Hugging Face Model Catalog on Azure, to gain insights into our practical applications 🤗.

Responsibilities

We seek talented individuals with a deep passion for Machine Learning (at the framework level) and Cloud Services:

• Integrating 🤗 models (Transformers/Diffusers) with different Cloud providers
• Ensuring models meet expected performance
• Designing and developing user-friendly, secure, and robust Developer Experiences & APIs
• Writing technical documentation, examples, and notebooks to demonstrate new features
• Sharing and advocating your work and its results within the community

About You

If you have experience and a keen interest in deploying machine learning systems to production and creating excellent developer experiences, you will thrive in this role. Ideal candidates will have:

• Extensive experience with Hugging Face Technologies (Transformers, Diffusers, Accelerate, PEFT, Datasets)
• Expertise in Deep Learning Frameworks, preferably PyTorch, with optional XLA understanding
• Strong knowledge of cloud platforms like AWS and services such as Amazon SageMaker, EC2, S3, CloudWatch, and their Azure and GCP equivalents
• Experience in building MLOps pipelines for containerizing models and solutions with Docker
• Familiarity with Typescript, Rust, MongoDB, and Kubernetes
• Ability to write clear documentation, examples, and work across the full product development lifecycle
• Bonus: Experience with Svelte & TailwindCSS

Why Work at Hugging Face

Diversity, Equity, and Inclusivity

We are committed to creating a culture that values diversity, equity, and inclusivity. We intentionally build a workplace where people feel respected and supported, regardless of their background. Hugging Face is an equal opportunity employer and does not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Professional Development

Work alongside some of the brightest minds in the industry. We encourage personal growth and provide reimbursement for relevant conferences, training, and education.

Well-Being and Flexibility

We offer flexible working hours, remote work options, and comprehensive health, dental, and vision benefits for employees and their dependents. Additionally, we provide parental leave and flexible paid time off.

Supportive Work Environment

We support our employees regardless of their location. Our office spaces are in NYC and Paris, but we have a distributed team. We also equip remote employees with necessary workstations to ensure success.

Employee Ownership

All employees have company equity as part of their compensation package. We want our teammates to share in our success as we strive to become a category-defining platform in machine learning and artificial intelligence.

Community Support

We believe major scientific advancements