Machine Learning Engineer, Document AI - US

Machine Learning Engineer, Document AI - US

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better.

We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 76K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.


About the Role

As a ML Engineer, you will work to improve the open-source accessibility of Document AI models and datasets. You will work towards creating datasets and training models from scratch, reproducing and building on top of the state-of-the-art Document AI techniques, in an effort to broaden open-source use cases and increase the availability of models with permissive licenses. You will get to work with a number of open-source tools, including but not limited to: Transformers, Datasets, TIMM, Diffusers, OpenCLIP, and others. You’ll be working primarily with PyTorch, and may eventually work on clusters as you scale small experiments to larger ones.

You'll get to foster one of the most active machine learning communities, and interact with Researchers, ML practitioners and data scientists on a daily basis through GitHub, our forums, or Slack.


About you

You have a passion for open-source, are passionate about making complex technology more accessible, and want to contribute to one of the fastest-growing ML ecosystems.

Some of our requirements for this role:

  • Experience working with multi-modal/document AI transformer models
  • Experience building and training models from scratch, working through hyperparameter tuning, debugging training performance and stability issues
  • Experience curating, improving, and debugging issues with large image and/or text datasets
  • Experience running experiments via slurm jobs/clusters.

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 background complement one another. We're happy to consider where you can make the biggest impact.


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 12 weeks of parental leave (20 for birthing mothers) and unlimited 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.

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