What are the responsibilities and job description for the Machine Learning Engineer Internship, Gradio - US Remote position at Hugging Face?
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
Gradio is the most widely used library to build and share machine learning demos, with more than 6m monthly downloads on PYPI. It is maintained by the Gradio team within Hugging Face.
We are currently working on a suite of AI tools to help users quickly understand and write Gradio code.The first is the Playground: a code editor on our website which can generate or update complete Gradio demos based on a user's query.
The main objective for a Machine Learning Engineering intern will be to expand this effort. We can leverage :500k Gradio spaces and thousands of existing prompts from users to build a sophisticated model pipeline with the proper context of how Gradio works.
More and more developers are relying on LLMs for assistance in writing code, but these LLMs often do not have proper context on how Gradio works. Gradio has evolved from a library to an ecosystem for machine learning developers, with custom components contributed from our community, Python and JS clients, and Gradio Lite. To advance these efforts and as Gradio's usage and developer community grows, it's important to invest in tools that can help users learn, build and contribute to Gradio.
About You
You're passionate about open source and making advanced ML tools accessible. You are someone who stays up to date with the latest machine learning trends and models. You love experimenting and have a high bias for action and results.
Some of our requirements for this role :
- Experience using modern deep learning libraries and LLM APIs and understanding tradeoffs between different models and APIs
- Knowledge of how to fine-tune LLMs, create retrieval-augmented generation pipelines, and use re-rankers for two-stage retrieval
- You're comfortable exploring and contributing to a codebase consisting of Python and Svelte-flavored JavaScript
- You have a "product mindset" -- like experimenting with different user interfaces to build products that are useful to to hundreds of thousands of users
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. 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.
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.
