Open-Source Machine Learning Engineer

🕒 May 29

🇫🇷 France – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 27%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Hugging Face

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

Artificial Intelligence • SaaS • Enterprise

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.

📋 Description

• Work to improve the open-source machine learning ecosystem • Mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch and vLLM • Interact with users and contributors across the broad open-source ML ecosystem • Help foster one of the most active machine learning communities • Collaborate with researchers, ML practitioners, and data scientists every day through GitHub, our forums, and Slack

🎯 Requirements

• Strong Python skills, with experience writing clean, well-tested, maintainable library code • Deep hands-on experience with a modern deep-learning framework, especially PyTorch (JAX or TensorFlow a plus) • Practical experience with the Hugging Face open-source stack (Transformers, Datasets, Accelerate) or comparable ML libraries • A public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHub • Solid understanding of modern machine learning and deep learning, including transformer architectures • Experience collaborating with a technical community in the open (GitHub issues and reviews, forums, Slack or Discord) • Fluent written English for asynchronous collaboration across a distributed, global community

🏖️ Benefits

• Health, dental, and vision benefits for employees and their dependents • Parental leave • Flexible paid time off • Flexible working hours and remote options • Reimbursement for relevant conferences, training, and education • Company equity as part of compensation package