Hugging Face
Hugging Face is a collaborative platform for the machine learning community, focusing on models, datasets, and applications. It offers a wide range of tools and resources for creating, discovering, and sharing machine learning models and datasets. Hugging Face provides open-source ML tools, including frameworks for PyTorch, TensorFlow, and JAX, as well as advanced solutions for businesses through its enterprise offerings. The company hosts thousands of models, datasets, and applications, serving as a central hub for AI research and development.
machine learning • natural language processing • deep learning
Cloud Machine Learning Engineer
October 19, 2024
🇺🇸 United States – Remote
⏰ Full Time
🟡 Mid-level
🟠 Senior
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
Hugging Face
Hugging Face is a collaborative platform for the machine learning community, focusing on models, datasets, and applications. It offers a wide range of tools and resources for creating, discovering, and sharing machine learning models and datasets. Hugging Face provides open-source ML tools, including frameworks for PyTorch, TensorFlow, and JAX, as well as advanced solutions for businesses through its enterprise offerings. The company hosts thousands of models, datasets, and applications, serving as a central hub for AI research and development.
machine learning • natural language processing • deep learning
📋 Description
• Join Hugging Face to advance accessible Machine Learning. • Build machine learning solutions used by millions leveraging cloud technologies. • Work on integrating open-source libraries with major cloud platforms or managed SaaS solutions. • Design & develop easy-to-use, secure, and robust Developer Experiences & APIs. • Write technical documentation, examples, and notebooks to demonstrate new features. • Share & advocate your work and results with the community.
🎯 Requirements
• 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, MongoDB, Kubernetes is helpful. • Ability to write clear documentation, examples, and definition and work across the full product development lifecycle. • Bonus: Experience with Svelte & TailwindCSS.
🏖️ Benefits
• Health, dental, and vision benefits for employees and their dependents. • Parental leave and flexible paid time off. • Flexible working hours and remote options. • Reimbursement for relevant conferences, training, and education. • Company equity as part of the compensation package.
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