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Machine Learning Engineer Internship, WebML - US Remote

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

Hugging Face maintains a large collection of open source machine learning libraries, including transformers, diffusers, and datasets, just to name a few. However, these are all implemented in Python, meaning they aren’t as easily accessible to JavaScript/TypeScript developers. So, in order to grow the Hugging Face ecosystem, we decided to build projects like transformers.js , diffusers.js , and huggingface.js with the primary goal of bridging the gap between web development and machine learning.

WebML (Web Machine Learning) unlocks a range of new possibilities for building web applications by enabling models to run locally in the browser. Combining on-device machine learning with the plethora of APIs that browsers provide, empowers developers to create low-latency, interactive, and privacy-focused applications that can scale and reach users without them needing to install anything!

This internship operates at the intersection of software engineering, machine learning, and open-source community building. The focus will be to expand the Hugging Face ecosystem to web developers through the creation and maintenance of ease-to-use JS/TS machine learning libraries.

By the end of the internship, the candidate will have touched on many aspects of web machine learning, including: converting and optimizing models for in-browser inference (ONNX, quantization), enabling models to run in-browser at near-native speeds (WebGPU, WebNN, WASM), building demo applications to showcase new features, and fostering a collaborative open-source community.

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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What You Should Know About Machine Learning Engineer Internship, WebML - US Remote, Hugging Face

Are you ready to dive into the exciting world of artificial intelligence? At Hugging Face, we're looking for a passionate Machine Learning Engineer Intern to join our WebML team, all from the comfort of your own home! We’re on a mission to democratize AI, and at this internship, you’ll be right at the heart of our rapidly growing platform. With over five million users and more than 100,000 organizations collaborating, there's a wealth of innovation in the air. You will help bridge the gap between web development and machine learning by working on projects like transformers.js and diffusers.js, so JavaScript and TypeScript developers can easily access our extensive libraries. Imagine empowering developers to create privacy-focused applications that run directly in the browser! You’ll be involved in optimizing models for in-browser inference and building demo applications to showcase your work. Plus, you'll contribute to nurturing an open-source community, making complex technologies accessible to everyone. We consider ourselves a diverse and inclusive team, welcoming different backgrounds and experiences, and we believe that your unique skills can help us grow even more. If you have a creative streak and a passion for making technology user-friendly, this is the perfect opportunity for you! Join us as we explore the fascinating intersection of software engineering, web development, and machine learning!

Frequently Asked Questions (FAQs) for Machine Learning Engineer Internship, WebML - US Remote Role at Hugging Face
What does a Machine Learning Engineer Internship at Hugging Face involve?

The Machine Learning Engineer Internship at Hugging Face focuses on enabling web developers to effortlessly use machine learning through projects like transformers.js and diffusers.js. You will work on bridging the gap between web development and machine learning by optimizing models for in-browser inference while exploring WebML technologies. The role also involves fostering an open-source community and creating demo applications to showcase new features.

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What skills are ideal for a Machine Learning Engineer Internship at Hugging Face?

Ideal candidates for the Machine Learning Engineer Internship at Hugging Face will possess strong programming skills, particularly in JavaScript and TypeScript, as well as a foundational understanding of machine learning principles. A passion for open-source development, creativity in solving problems, and a desire to make complex technology more accessible to developers are also great qualities to bring to the table.

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Can I work remotely as a Machine Learning Engineer Intern at Hugging Face?

Yes, the Machine Learning Engineer Internship at Hugging Face is fully remote! The company embraces flexible working hours and offers the chance to collaborate with colleagues around the globe, ensuring you can balance work with your personal commitments.

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What distinguishes Hugging Face's Machine Learning Engineer Internship from others?

Hugging Face's Machine Learning Engineer Internship stands out due to its commitment to open-source development and community building. Interns have the opportunity to work on impactful projects that directly contribute to the rapidly growing machine learning ecosystem, while also personal and professional development opportunities, such as conference reimbursements, are generously provided.

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How does Hugging Face support its interns during the Machine Learning Engineer Internship?

Hugging Face supports its interns by providing a flexible working environment, the ability to learn from industry experts, and the resources necessary for success. Interns are supplied with workstation equipment as needed, access to training and development resources, and the opportunity to collaborate within a diverse community of talented individuals.

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What are the growth opportunities after the Machine Learning Engineer Internship at Hugging Face?

After completing the Machine Learning Engineer Internship at Hugging Face, interns have the potential to transition into full-time roles or other internship opportunities within the company. The skills gained during the internship – including machine learning, software engineering, and community building – are highly valuable and in demand, opening various career paths.

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Is previous experience in machine learning required for the Machine Learning Engineer Internship at Hugging Face?

While previous experience in machine learning can be advantageous, it is not a strict requirement for the Machine Learning Engineer Internship at Hugging Face. The company encourages applicants with a strong foundation in programming and an eagerness to learn about machine learning technology to apply, as mentorship and training resources will be available to help you thrive.

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Common Interview Questions for Machine Learning Engineer Internship, WebML - US Remote
What interests you about the Machine Learning Engineer Internship at Hugging Face?

Express genuine excitement about the opportunity to work at Hugging Face, focusing on its mission to democratize AI and the chance to contribute to popular open-source projects. Discuss how your personal values align with the company's diverse culture and openness to creativity.

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Can you explain a recent machine learning project you have worked on?

When discussing a past project, structure your answer using the STAR method (Situation, Task, Action, Result). Detail the project objective, your specific role, the machine learning techniques used, and the successful outcomes achieved, emphasizing how that experience correlates with Hugging Face's current goals.

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How do you approach optimizing machine learning models?

Discuss your methodology for optimizing machine learning models, which could include techniques like quantization, using efficient architectures, or leveraging specific libraries and tools. Also, mention the importance of testing and validating the model's performance to ensure high accuracy.

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What are your thoughts on the role of open-source in machine learning development?

Share insights on the value of open-source contributions in facilitating collaboration, innovation, and transparency within the machine learning community. Explain how you envision contributing to Hugging Face's open-source ecosystem and fostering an inclusive developer community.

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How do you stay current with new developments in machine learning technology?

Highlight your commitment to continuous learning through resources like academic journals, online courses, webinars, and participating in technology communities. This showcases your proactive attitude towards staying informed about innovations in machine learning.

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Can you share an example of a time you collaborated on a project?

Choose a collaborative project that demonstrates your ability to work effectively in a team. Describe your role, the contributions of your teammates, the communication strategies you employed, and how the teamwork contributed to achieving project goals.

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What programming languages and tools are you proficient in related to machine learning?

Highlight proficiency in essential programming languages like Python and JavaScript/TypeScript, as well as your experience with various machine learning libraries and frameworks, such as TensorFlow, PyTorch, or Hugging Face’s own libraries. Be sure to discuss how you can apply these skills to the intern role.

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Describe a challenge you faced in a machine learning project and how you overcame it.

Choose a meaningful challenge, explain the context behind it, and detail the steps you took to overcome it. This could involve troubleshooting code, refining models, or collaborating with others to find a solution. Emphasize the lessons learned through the experience.

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What do you believe is the most exciting development in machine learning currently?

Share your thoughts on groundbreaking advancements, such as AI ethics, federated learning, or major improvements in natural language processing. Relate this back to Hugging Face’s work and your own aspirations to be part of such advancements.

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Why do you think you would be a good fit for the Machine Learning Engineer Internship at Hugging Face?

Reflect on your skills, passion for technology, and alignment with Hugging Face’s values and mission. Be sure to highlight your eagerness to learn, work in a collaborative environment, and your commitment to contributing meaningfully to the team and the open-source community.

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Internship, remote
DATE POSTED
November 28, 2024

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