Machine Learning Engineer Internship, AI Energy Score

Hugging Face is leading the charge in democratizing good AI through their rapidly expanding platform that serves over 5 million users and 100,000 organizations. Their impact in the open-source community is evident with 400k+ Github stars across their libraries.

This internship role focuses on a crucial aspect of modern AI development - the energy efficiency of machine learning models. As part of the AI Energy Score project, you'll be conducting experiments and analysis to evaluate the energy consumption patterns of various models across different deployment scenarios, including hardware configurations, optimization techniques, and serving stacks.

The position offers a unique opportunity to work with industry-leading experts in a company that values diversity, equity, and inclusivity. Hugging Face provides a supportive environment for professional growth, offering reimbursement for conferences, training, and education. The company maintains a flexible work culture with remote options and well-equipped workstations for all employees.

What makes this role particularly exciting is its combination of technical challenge and environmental impact. You'll be contributing to understanding and potentially improving the energy efficiency of AI models, which is becoming increasingly important as the field grows. The company's strong commitment to open-source collaboration and community support creates an ideal environment for learning and making meaningful contributions to the ML/AI community.

Working at Hugging Face means joining a team that values continuous growth, impact-driven development, and inclusive culture. Whether you're working from one of their offices in the US, Canada, or Europe, or remotely, you'll be part of a community that's actively shaping the future of AI while considering its environmental implications.