ML Engineer Internship, Enhance Hardware Efficiency - EMEA Remote

Here at Hugging Face, we're on a quest to improve and democratize Machine Learning. In the process, we aim to boost the progress of technology for the better.

We've built the fastest-growing open-source library of pre-trained models in the world. With over 500K+ models and 250K+ stars on GitHub, more than 15,000 companies are utilizing Hugging Face technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly.

About the Role

This internship aims to enhance the performance of transformer-based AI models through researching how to exploit model compilation and graph rewriting to optimize hardware effectiveness and performance. A profound exploration into various AI model optimization techniques, including device placement, subgraph fusion, dispatching, and others will be conducted. These techniques will be employed to facilitate performance enhancements across various AI model structures and tasks.

About You

If you're passionate about open-source, interested in making complex technology more available to engineers and artists, and eager to contribute to one of the rapidly growing Machine Learning ecosystems, we're excited to see your application!

If you're keen to join us, but don't meet all the criteria above, we still encourage you to apply! We're constructing a diverse team where skills, experiences, and backgrounds mesh together. We're open to considering where you could make the largest impact.

More about Hugging Face

We are actively striving to develop a culture that appreciates diversity, equity, and inclusiveness. We're purposefully creating a workplace in which people feel respected and supported—regardless of who they are or where they originate from. We believe this is essential for building a successful company and community. Hugging Face is an equal opportunity employer and we do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We prioritize development. You'll be working with some of the most brilliant individuals in our field. We are an organization with a bias for impact and are constantly challenging ourselves to keep growing. All employees are offered reimbursement for relevant conferences, training, and education.

We care about your well-being. We provide flexible working hours and remote options. We support our employees wherever they are located. While we have offices worldwide, particularly in the US, Canada, and Europe, we're highly distributed and all remote employees have the opportunity to visit our offices. If required, we'll also equip your workstation to ensure your success.

We support the community. We believe major scientific advancements result from collaboration across the field. Join a community that supports the Machine Learning/AI community.