Cloud Machine Learning Engineer - EMEA remote at Hugging Face

France

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

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 (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, and Kubernetes
Ability to write clear documentation, examples, and work across the full product development lifecycle
Experience with and interest in deploying machine learning systems to production and building great developer experiences
Bonus: Experience with Svelte & TailwindCSS

Responsibilities

Help build machine learning solutions used by millions leveraging cloud technologies
Integrate Hugging Face's open-source libraries like Transformers and Diffusers with major cloud platforms or managed SaaS solutions
Bridge and integrate transformers/diffusers models with different Cloud providers
Ensure the above models meet the expected performance
Design & Develop easy-to-use, secure, and robust Developer Experiences & APIs for users
Write technical documentation, examples, and notebooks to demonstrate new features
Share & Advocate your work and the results with the community

Skills

Key technologies and capabilities for this role

TransformersDiffusersAWSAzurewatsonx.aiMachine LearningCloud PlatformsAPIsTechnical Documentation

Questions & Answers

Common questions about this position

Is this position remote?

Yes, this is a remote position available in the EMEA region.

What is the salary for this role?

This information is not specified in the job description.

What skills are required for this Cloud Machine Learning Engineer role?

Required skills include deep experience with Hugging Face Technologies like Transformers and Diffusers, expertise in PyTorch, strong knowledge of cloud platforms such as AWS or Azure, and experience building MLOps pipelines with Docker.

What is the company culture like at Hugging Face?

Hugging Face is actively working to build a culture that values diversity, equity, and inclusivity.

What makes a strong candidate for this role?

A strong candidate has deep experience and passion for Machine Learning at the framework level and Cloud Services, particularly integrating Hugging Face libraries like Transformers and Diffusers with cloud providers, along with skills in PyTorch, MLOps, and building developer experiences.

Hugging Face

Develops advanced NLP models for text tasks

About Hugging Face

Hugging Face develops machine learning models focused on understanding and generating human-like text. Their main products include advanced natural language processing (NLP) models like GPT-2 and XLNet, which can perform tasks such as text completion, translation, and summarization. Users can access these models through a web application and a repository, making it easy to integrate AI into various applications. Unlike many competitors, Hugging Face offers a freemium model, allowing users to access basic features for free while providing subscription plans for advanced functionalities. The company also tailors solutions for large organizations, including custom model training. Hugging Face aims to empower researchers, developers, and enterprises to utilize machine learning for text-related tasks.

New York City, New YorkHeadquarters

2016Year Founded

$384.9MTotal Funding

SERIES_DCompany Stage

Enterprise Software, AI & Machine LearningIndustries

201-500Employees

Benefits

Flexible Work Environment

Health Insurance

Unlimited PTO

Equity

Growth, Training, & Conferences

Generous Parental Leave

Risks

Salesforce's exclusive partnerships may limit Hugging Face's access to training datasets.

Microsoft's rStar-Math technique could outperform Hugging Face's NLP models in specific tasks.

DeepSeek-V3's release may intensify competition in the ultra-large model space.

Differentiation

Hugging Face offers a massive library of over one million AI models.

The company provides a thriving online community for open-source AI collaboration.

Hugging Face's freemium model allows easy access to advanced NLP tools.

Upsides

Collaboration with Microsoft could enhance small model performance in mathematical reasoning.

Partnership with DeepSeek may boost Hugging Face's ultra-large model capabilities.

Integration with Salesforce's ProVision could improve multimodal AI capabilities.

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