Machine Learning Engineer Internship, Gradio
Description For Machine Learning Engineer Internship, Gradio
Hugging Face, the fastest-growing AI platform with 5M+ users and 100k+ organizations, is seeking a Machine Learning Engineer Intern for their Gradio team. Gradio, their widely-used library for building ML demos (6M+ monthly downloads), needs help expanding their AI tools suite. The role focuses on developing sophisticated model pipelines using ~500k Gradio spaces and user prompts to improve code generation and understanding.
The ideal candidate will work on the Playground code editor and help create AI tools that assist users in writing Gradio code. This position offers a unique opportunity to impact hundreds of thousands of users while working with cutting-edge ML technologies. The role requires experience with deep learning libraries, LLM APIs, and full-stack development (Python/JavaScript).
Working at Hugging Face means joining a diverse, inclusive community that values development and well-being. The company offers flexible remote work, educational support, and the chance to collaborate with industry leaders. This internship is perfect for someone passionate about open source, machine learning, and making advanced ML tools accessible to developers worldwide.
Responsibilities For Machine Learning Engineer Internship, Gradio
- Expand AI tools suite for Gradio code understanding and generation
- Work on the Playground code editor
- Leverage ~500k Gradio spaces and user prompts to build model pipeline
- Contribute to making advanced ML tools accessible
Requirements For Machine Learning Engineer Internship, Gradio
- Experience using modern deep learning libraries and LLM APIs
- Knowledge of how to fine-tune LLMs, create retrieval-augmented generation pipelines, and use re-rankers
- Comfortable with Python and Svelte-flavored JavaScript
- Product mindset and experience with user interfaces
- Cover letter explaining interest in open-source at Hugging Face
Benefits For Machine Learning Engineer Internship, Gradio
- Flexible working hours
- Remote work options
- Office visits opportunity
- Workstation support
- Conference and training reimbursement
- Educational development support
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