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ML Research Engineer Internship, OS Agents - 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

2025 will be the year of Agents.

LLM agents, what are these? In short, agentic systems are a way to connect an LLM to the outside world, to let it perform actions and observations. The promises of such a setup are immense : it enables an LLM to get external knowledge to ground its reasoning, use reliable tools for specific tasks, and even self-correct errors through additional iterations.

An agentic system requires a powerful enough LLM to reason and plan actions. Now with the progress of LLMs in general and specifically open models overtaking closed ones, we have all weapons to build great agents. So Hugging Face is launching a moonshot in that direction.

Building agents is both exciting and challenging as it lies at the intersection of post-training, inference, orchestration as well as UX design.

During this internship you will work specifically on agents that take screen recordings from any GUI, and act through a mouse/keyboard setup. You may have seen such models from other companies: we’ll make them better and open.

This work will include the whole agent stack, from improving the framework, to preparing fine-tuning datasets, training recipes, and inference orchestration. You will leverage our compute CPU and H100 clusters for large scale processing and model training. Finally we’ll release any code we built, as well as the model serving as a foundation for the community to build on.

Checkout hf.co/science for more information about the science team at Hugging Face.

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.

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.

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What You Should Know About ML Research Engineer Internship, OS Agents - US Remote, Hugging Face

Are you ready to dive into the exciting world of machine learning? At Hugging Face, we’re thrilled to offer a unique opportunity as an ML Research Engineer Intern, specifically on our OS Agents team, where you’ll be part of a dynamic and passionate group that's revolutionizing AI. In 2025, we're gearing up for the year of Agents, focusing on how large language models (LLMs) can interact with the world in impactful ways. You'll be engaged in building agentic systems that allow LLMs to perform actions and gather external knowledge, thereby enhancing their reasoning capabilities. This role is an amazing blend of technology and creativity, as you will work on improving frameworks, preparing fine-tuning datasets, and orchestrating inference. Plus, you’ll have access to our advanced CPU and H100 clusters for your projects! At Hugging Face, we are committed to open-source principles, and you’ll have the chance to create impactful contributions that can benefit a vast community. You've come to the right place if you’re passionate about making complex technology simpler and more accessible. We believe in building a diverse team, and even if you don’t meet every requirement, if you have enthusiasm and a unique perspective, we want to hear from you. So, if you’re excited about making a difference in a fast-growing ML ecosystem and working alongside some of the industry’s brightest minds, we can’t wait for you to apply! Don’t forget to submit a cover letter showcasing your interest in open-source and what skills you bring to the table!

Frequently Asked Questions (FAQs) for ML Research Engineer Internship, OS Agents - US Remote Role at Hugging Face
What are the main responsibilities of the ML Research Engineer Internship at Hugging Face?

As an ML Research Engineer Intern at Hugging Face, your key responsibilities will involve contributing to the development of agentic systems by enhancing frameworks, creating fine-tuning datasets, and managing inference orchestration. You'll work with modern LLMs to improve functionalities, enabling them to perform actions based on user inputs and observations, which is at the heart of our mission to democratize AI.

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What qualifications do I need for the ML Research Engineer Internship at Hugging Face?

For the ML Research Engineer Internship at Hugging Face, candidates should ideally possess a strong foundation in machine learning and computer science principles. Familiarity with open-source projects, programming skills in Python, and an understanding of LLMs are highly advantageous. Moreover, a creative mindset and a passion for making AI accessible can set applicants apart in this collaborative environment.

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How does Hugging Face support its interns working as ML Research Engineers?

Hugging Face actively supports its interns working in the ML Research Engineer role through flexible working hours, remote options, and access to essential resources, including top-tier computational support. Additionally, the team values continuous development, offering reimbursement for relevant conferences and training. This environment empowers interns to grow and make a meaningful impact.

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What can I learn during my internship as an ML Research Engineer at Hugging Face?

During your internship as an ML Research Engineer at Hugging Face, you’ll gain invaluable hands-on experience in the field of machine learning, particularly concerning agent systems. You will work with cutting-edge technologies and collaborate with experts, allowing you to deepen your technical skills, enhance your problem-solving capabilities, and better understand the open-source community's nuances.

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Can I apply for the ML Research Engineer Internship at Hugging Face if I don't meet all qualifications?

Yes! At Hugging Face, we encourage candidates who may not meet every single qualification for the ML Research Engineer Internship to still apply. We value diverse backgrounds and perspectives, and we're always looking for individuals with a genuine passion for machine learning and a unique set of experiences that can complement our team.

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Common Interview Questions for ML Research Engineer Internship, OS Agents - US Remote
Can you describe your experience with machine learning and specifically with LLMs?

When answering this question, highlight your educational background and any relevant projects you've undertaken that involve machine learning and large language models. Discuss specific frameworks or libraries you've worked with, such as TensorFlow or PyTorch, and share any personal projects or contributions you've made to open-source that showcase your skills.

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What attracts you to the ML Research Engineer Internship at Hugging Face?

Focus on your enthusiasm for open-source projects and AI technology's transformative potential during your response. Discuss how Hugging Face’s commitment to democratizing AI aligns with your values and future aspirations. Highlight specific aspects of the role, like working on agentic systems, to convey your genuine interest.

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How would you approach improving an existing ML model?

In answering this, describe a systematic approach where you analyze the current model's performance metrics, review training procedures, and identify areas for improvement. Share specific techniques you've used or would consider, such as data augmentation, hyperparameter tuning, or exploring alternative architectures.

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What are your strategies for managing large datasets?

When responding, discuss any experience you have with data preprocessing, cleaning, and augmenting large datasets. Mention tools and libraries you’ve utilized, like Pandas or Dask, and how you ensure efficient data handling and storage to enhance model training.

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Can you discuss a complex problem you solved in a previous project?

Provide a specific example of a challenging problem from your past work, detailing the context, your thought process, and the steps you took to arrive at a solution. Highlight any collaboration with others and what you learned from the experience, focusing on your growth and adaptability.

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How do you stay updated with the latest advancements in machine learning?

Mention various resources you utilize, such as research papers, online courses, blogs, and machine learning forums or communities. Highlight your commitment to continuous learning, and ensure to touch on any networking or collaborative opportunities you engage in, especially related to open-source contributions.

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What role do you believe creativity plays in machine learning?

Emphasize the importance of creativity in problem-solving and innovation within machine learning. Discuss how thinking outside the box can lead to novel algorithms or solutions, and mention any instances where your creative thinking led to project advancements.

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Describe your experience with programming and any languages you are proficient in.

Specify the programming languages you are most proficient in, especially Python, which is widely used in machine learning. Highlight projects where you've applied your coding skills, emphasizing collaboration and any notable libraries you have used, such as scikit-learn, TensorFlow, or PyTorch.

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How would you handle a disagreement with a teammate regarding a project approach?

Share your conflict resolution approach by describing how you would communicate openly with your teammate, listen to their perspective, and seek a compromise. Emphasize the importance of collaborative dialogue and finding a shared goal in achieving the best outcome for the team.

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What motivates you to work in the field of open-source machine learning?

Reflect on your passion for community collaboration and knowledge sharing within the open-source machine learning landscape. Discuss how you appreciate the collective efforts that drive innovation and your desire to contribute to this vibrant ecosystem through the ML Research Engineer Internship at Hugging Face.

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DATE POSTED
December 6, 2024

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