Hugging Face

Cloud Machine Learning Engineer

Hugging Face

full-time

Posted on:

Location Type: Remote

Location: United States

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Tech Stack

AWSAzureCloudDockerEC2Google Cloud PlatformKubernetesMongoDBPyTorchRustSvelteTypeScript

About the role

  • Bridging and 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.
  • Write technical documentation, examples and notebooks to demonstrate new features
  • Sharing & Advocating your work and the 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, 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
  • We offer health, dental, and vision benefits for employees and their dependents.
  • We also offer parental leave and flexible paid time off.
  • Flexible working hours and remote options.
  • Reimbursement for relevant conferences, training, and education.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Hugging Face TechnologiesTransformersDiffusersAcceleratePEFTDatasetsDeep Learning FrameworkPyTorchMLOpsDocker
Soft Skills
clear documentationadvocating workcommunity engagement