Machine Learning Engineer Internship, WebML - US Remote Job at Hugging Face, Largo, FL

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  • Hugging Face
  • Largo, FL

Job Description

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 more than 500K+ models and 250K+ stars on GitHub, over 15.000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.

About the Role

Hugging Face maintains a large collection of open source machine learning libraries, including transformers, diffusers, and datasets, just to name a few. However, these are all implemented in Python, meaning they aren’t as easily accessible to JavaScript/TypeScript developers. So, in order to grow the Hugging Face ecosystem, we decided to build projects like transformers.js , diffusers.js , and huggingface.js with the primary goal of bridging the gap between web development and machine learning.

WebML (Web Machine Learning) unlocks a range of new possibilities for building web applications by enabling models to run locally in the browser. Combining on-device machine learning with the plethora of APIs that browsers provide, empowers developers to create low-latency, interactive, and privacy-focused applications that can scale and reach users without them needing to install anything!

This internship operates at the intersection of software engineering, machine learning, and open-source community building. The focus will be to expand the Hugging Face ecosystem to web developers through the creation and maintenance of ease-to-use JS/TS machine learning libraries.

By the end of the internship, the candidate will have touched on many aspects of web machine learning, including: converting and optimizing models for in-browser inference (ONNX, quantization), enabling models to run in-browser at near-native speeds (WebGPU, WebNN, WASM), building demo applications to showcase new features, and fostering a collaborative open-source community.

About You

If you love open-source but also have an eye for art and creativity, are passionate about making complex technology more accessible to engineers and artists, and want to contribute to one of the fastest-growing ML ecosystems, then we can't wait to see your application!

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 might be able to 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 support our employees wherever they are. While we have office spaces around the world, especially in the US, Canada, and Europe, 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 support the community. We believe significant scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.

Job Tags

Work at office, Remote work, Flexible hours,

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