Hugging Face is hiring a
Cloud Machine Learning Engineer, Remote - United States

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Hugging Face

πŸ’΅ ~$125k-$238k
πŸ“United States

Summary

The job is for a Cloud Machine Learning engineer to help build machine learning solutions using Hugging Face's open-source libraries and integrate them with various cloud platforms. The ideal candidate has deep experience with Hugging Face Technologies, expertise in Deep Learning Framework (PyTorch), knowledge of cloud platforms like AWS and Azure, and ability to write clear documentation.

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

Responsibilities

  • Bridging and integrating πŸ€— 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
  • Write technical documentation, examples and notebooks to demonstrate new features
  • Sharing & Advocating your work and the results with the community

Preferred Qualifications

  • 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
  • Bonus: Experience with Svelte & TailwindCSS

Benefits

  • Flexible working hours and remote options
  • Health, dental, and vision benefits for employees and their dependents
  • Parental leave and flexible paid time off
  • Company equity as part of compensation package
  • Relevant conferences, training, and education reimbursement
  • Opportunity to visit office spaces in NYC and Paris

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