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
The energy requirements of machine learning models have been rising in recent years, raising concerns regarding the impacts of this on energy grids and the environment.
Building upon the AI Energy Score project, this internship will continue experimentation and analysis to get a better understanding of the energy efficiency of different models and deployment contexts (hardware, optimization techniques, serving stacks).
About You
If you love open-source but also have an eye for art and creativity, are passionate about making complex technology more accessible to engineers and artists, and want to contribute to one of the fastest-growing ML ecosystems, then we can't wait to see your application!
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 background 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.
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Are you ready to kickstart your career in AI? Hugging Face is thrilled to offer a Machine Learning Engineer Internship as part of our innovative AI Energy Score project, specifically for our EMEA remote team! At Hugging Face, we are committed to democratizing good AI, having gathered a sprawling community of over 5 million users and 100,000 organizations. With an impressive tally of 1 million models and counting, we’re building the fastest growing platform for AI enthusiasts. As a Machine Learning Engineer Intern, you’ll get the chance to dive into the exciting realm of energy efficiency in machine learning models. Given the rising concerns over energy use within AI, your role will focus on experimentation and analysis, utilizing various deployment contexts like hardware and optimization techniques. If you’re someone with a passion for making complex technology accessible and love the open-source environment, this opportunity could be a perfect fit. At Hugging Face, we prioritize diversity, equity, and inclusion, and we encourage all qualified individuals to apply, even if you don’t tick every box listed. Buckle up for an impactful journey where learning and personal development are at the forefront—your ideas and creativity will be welcomed with open arms. We support our remote employees with flexible hours, comprehensive reimbursement for conferences and training, and even opportunities to visit our office spaces worldwide. Join us on this adventure in empowering the ML/AI community!
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