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Open-Source Machine Learning Engineer - EMEA Remote

Hugging Face Open
Remote Paris Full-time Mid-level Machine Learning Engineering

At a glance

Mid-level Machine Learning Engineering role at Hugging Face. Remote, France · full-time.

Pay not stated Machine Learning Engineering salary

RoleMachine Learning Engineering
SeniorityMid-level
LocationParis
WorkplaceRemote
EmploymentFull-time
PostedMay 29, 2026
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Improve existing open-source machine learning libraries, including Transformers, Datasets, PyTorch and vLLM
  • Build tools that help machine learning users contribute to and use open-source libraries
  • Work with researchers, practitioners and data scientists through GitHub, forums and Slack
  • Collaborate with contributors and users across the open-source machine learning community

What you bring

  • Strong Python skills for writing clean, tested and maintainable library code
  • Hands-on experience with a deep-learning framework, especially PyTorch, plus working knowledge of modern ML and transformer architectures
  • Practical experience with Hugging Face libraries or comparable machine learning tools
  • Public open-source contributions others can review, such as merged changes to ML or data libraries
  • Fluent written English and experience working with technical communities in public

Who this fits

This role suits an engineer who enjoys open-source collaboration and making complex machine learning technology more accessible. It is remote in EMEA, with Paris listed as the location. The posting encourages applicants who do not meet every listed qualification to apply.

From the employer

At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github.

About the Role

As an Open-Source Machine Learning Engineer, you'll work to improve the open-source machine learning ecosystem. You'll mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch and vLLM, and you'll interact with users and contributors across the broad open-source ML ecosystem. We'll brainstorm with you to put you in a position to do the work that interests you and that is impactful.

You'll help foster one of the most active machine learning communities, helping users contribute to and use the tools you build. You'll work with researchers, ML practitioners, and data scientists every day through GitHub, our forums, and Slack.

About You

You have a public track record of open-source work, and you enjoy collaborating with a community out in the open on GitHub. You love open source, you're passionate about making complex technology more accessible, and you want to contribute to one of the fastest-growing ML ecosystems. If that's you, we can't wait to see your application.

What you'll need

  • 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

Nice to have

  • Experience maintaining an open-source project
  • Prior contributions to Transformers, Datasets, Accelerate, or similar libraries
  • Familiarity with distributed training, inference optimization, or GPU/accelerator performance work
  • Experience training or fine-tuning models at scale

A note on fit

If you're interested in joining us but don't tick every box above, we still encourage you to apply. We're building a diverse team whose skills, experiences, and backgrounds complement one another, and we're happy to consider where you might make the biggest impact.

One more thing

At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “GPU-poor and proud 🤗”. No trick, no catch, it just tells us a real person is on the other side.

More about Hugging Face

We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.

We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.

We support our employees wherever they are. While we have office spaces in NYC and Paris, we're very distributed and all remote employees have the opportunity to visit our offices. If needed, we'll also outfit your workstation to ensure you succeed.

We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.

We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

Requirements

Please provide a cover letter mentioning why you would like to work in open-source at Hugging Face. We encourage you to mention your skills, potential expertise, and topics on which you would like to work.

Opportunity

Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Machine Learning EngineeringRemote

Find me work

By the team behind remoteroles.

Find me work
Opportunity

Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.