Machine Learning Engineer Internship

At Hugging Face, we’re on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 5 million users & 100k organizations who collectively shared over 1M models, 300k datasets & 300k apps. Our open-source libraries have more than 400k+ stars on Github.

About the Role

At Hugging Face, we’re leading the AI revolution with a mission to democratize machine learning. Through our open-source libraries, state-of-the-art models, and curated datasets, we empower developers and researchers to build cutting-edge AI solutions. Besides, to ensure our models run seamlessly across a diverse range of hardware platforms, our ML Optimization team partners with some of the world’s top hardware innovators, including AWS Inferentia and Trainium, AMD CPUs and Instinct GPUs, Nvidia GPUs, Google TPUs, Intel CPUs, and Habana accelerators.

At the heart of these collaborations is Optimum, our open-source library that bridges the Hugging Face ecosystem with specific hardware. Optimum and its sub-packages are pivotal in optimizing performance and accessibility, helping developers maximize efficiency and scalability.

As an intern on the ML Optimization team, you’ll play a key role in shaping the future of AI. Your contributions will involve developing and refining cutting-edge solutions for widely-used and emerging hardware platforms, sharing these advancements with the Hugging Face community, and enabling researchers and developers worldwide to access the best tools and technologies. This is your opportunity to make a tangible impact on the AI landscape while working alongside world-class experts and forward-thinking hardware providers.

Key Responsibilities

1. Develop an online exporter tool: Create a user-friendly online tool to convert Hugging Face models for specific hardware platforms leveraging Optimum.

2. Bake the recipes: Author comprehensive guides to help users deploy Hugging Face models on various hardware platforms, including detailed instructions and best practices.

3. Design User Flow: Develop a seamless flow to guide users from traditional Hugging Face libraries (like Transformers and Diffusers) to alternative hardware backends. This includes integrating these solutions into the Hugging Face Hub and our partners’ platforms.

4. Optimize Hardware Selection: Conduct inference experiments across different hardware backends to identify the strengths and weaknesses of each platform under various scenarios. Provide clear guidelines to help users select the best hardware for their specific tasks.

5. Advocate and Communicate Insights: Collaborate with the Hugging Face Advocacy team to share your findings and insights through various channels, including blog posts, tweets, leaderboards, Spaces, and YouTube videos. You will educate and inspire the community about the importance of hardware in AI.

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.

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.