At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders. We are looking for a Cloud Machine Learning engineer responsible to help build machine learning solutions used by millions leveraging cloud technologies.
You will work on integrating Hugging Face's open-source libraries like Transformers and Diffusers, with major cloud platforms or managed SaaS solutions. This role involves bridging and integrating models with different cloud providers, ensuring the models meet expected performance, designing and developing easy-to-use, secure, and robust developer experiences and APIs for our users, writing technical documentation, examples and notebooks to demonstrate new features, and sharing and advocating your work and the results with the community.
The ideal candidate will have deep experience building with Hugging Face Technologies, including Transformers, Diffusers, Accelerate, PEFT, Datasets, expertise in Deep Learning Framework, preferably PyTorch, optionally XLA understanding, strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, S3, CloudWatch and/or Azure and GCP equivalents, experience in building MLOps pipelines for containerizing models and solutions with Docker, familiarity with Typescript, Rust, and MongoDB, Kubernetes are helpful, ability to write clear documentation, examples and definition and work across the full product development lifecycle, and bonus experience with Svelte & TailwindCSS.
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.
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