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Machine Learning Engineer Internship, TRL - 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

In the past year the focus of building LLMs has gradually shifted from pretraining to post-training. This means spending more and more time on figuring out how to get models follow instructions reliably, use tools and generally align with certain values. With over 10k Github stars and close to 1M monthly installs the TRL library has become one of the go-to libraries for post-training. It scales flexibly from a single GPU to large clusters of GPUs using PEFT and ZeRO and offers a wide range of trainers for the latest post training techniques such as PPO or DPO and many more. In addition it includes a user friendly CLI that allows training models with a single command.

During this internship, you will collaborate with the research team to integrate cutting-edge methods into the library, maintain a clean and scalable codebase, and ensure its usability through thoughtful documentation. You’ll actively engage with the TRL community by responding to issues, gathering feedback, and fostering collaboration through thoughtful discussions and support, ensuring the library continues to meet developers' needs. Your contributions will directly influence thousands of developers globally, advancing the adoption of state-of-the-art post-training techniques and laying the groundwork for the next generation of customizable, instruction-following LLMs.

About You

We are looking for someone with knowledge and experience in some of the following areas:

  1. Machine Learning: Fine-tuning large language models (LLMs) or vision-language models (VLMs), and optimisation techniques.
  2. Software Development: Proficiency in Python, PyTorch, and frameworks like Hugging Face Transformers, with experience in distributed training and GPU acceleration.
  3. Open-Source: Familiarity with Git/GitHub workflows, community engagement, documentation, and collaborative development.
  4. Research and Experimentation: Exposure to cutting-edge ML research, benchmarking, and testing fine-tuning methods.
  5. Tooling and Maintenance: Building tools to streamline workflows, ensuring software stability, backward compatibility, versioning, and delivering reliable releases.
  6. Communication and Outreach: Writing blog posts, tutorials, and sharing updates on platforms like LinkedIn to engage with the community and make complex concepts accessible to a wider audience.

You’re passionate about open-source innovation and making advanced ML tools accessible globally. You value continuity in software development, ensuring users have a dependable and evolving library to rely on.

Even if you don’t check every box, we encourage you to apply—we value diverse skills, perspectives, and experiences that complement our mission.

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 Machine Learning Engineer Internship, TRL - US Remote, Hugging Face

Are you ready to kickstart your career in artificial intelligence? Join Hugging Face as a Machine Learning Engineer Intern and become part of our exciting mission to democratize good AI! We’re building the fastest-growing platform for AI builders, attracting over 5 million users and 100,000 organizations, all sharing resources like models and datasets like never before. As an intern, you'll dive into the world of post-training techniques, collaborating with our research team to enhance our renowned TRL library. Imagine contributing to a tool that helps developers create customizable LLMs while engaging with the vibrant community around it. Your role will involve integrating state-of-the-art methodologies into the library, ensuring it's not only robust but also user-friendly through smart documentation and community engagement. You'll be fine-tuning models, coding with Python and PyTorch, and even sharing your insights through tutorials and blog posts to make complex ideas accessible. We value your unique perspective and experience, whatever your background may be, as long as you’re passionate about open-source innovation and ML tools. Not to mention, working remotely gives you the freedom to balance work and life, and we support you with resources for success. Come join us at Hugging Face, where your work will have a meaningful impact on the global developer community!

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

As a Machine Learning Engineer Intern at Hugging Face, you will collaborate with our dedicated research team to integrate cutting-edge methods into the TRL library. Your tasks will include maintaining the codebase, creating documentation, and engaging with the community, all designed to enhance the usability of our library and advance AI technology.

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What qualifications are needed for the Machine Learning Engineer Internship at Hugging Face?

To be considered for the Machine Learning Engineer Internship at Hugging Face, candidates should have experience in machine learning, proficiency in Python and PyTorch, and familiarity with open-source development. We appreciate diverse backgrounds and encourage applicants who are eager to learn and grow within the field.

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What impact will I have as a Machine Learning Engineer Intern at Hugging Face?

As a Machine Learning Engineer Intern, your work will directly influence thousands of developers globally. By enhancing the TRL library, you’ll help shape the future of customizable, instruction-following large language models, ensuring they meet the needs of the developer community.

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Is the Machine Learning Engineer Internship at Hugging Face remote?

Yes! The Machine Learning Engineer Internship at Hugging Face is a remote position, allowing you to work from anywhere. This flexibility enables you to balance work and personal life while contributing to a meaningful mission.

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How does Hugging Face support the growth of interns in the Machine Learning Engineer Internship?

Hugging Face supports intern growth by providing access to training and education reimbursements, allowing you to attend conferences and workshops. Additionally, you'll collaborate with experienced professionals who are dedicated to your mentorship and professional development.

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What technologies will I work with in the Machine Learning Engineer Internship at Hugging Face?

During your internship as a Machine Learning Engineer at Hugging Face, you will work primarily with Python, PyTorch, and the Hugging Face Transformers library. You'll also gain experience with cutting-edge post-training techniques and tools designed to enhance model performance.

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What kind of projects will I be involved in during the Machine Learning Engineer Internship at Hugging Face?

As an intern, you will engage in projects that focus on integrating and enhancing post-training techniques within the TRL library, improving code usability, and engaging with the community. Your work will provide valuable resources for developers in the AI space.

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Common Interview Questions for Machine Learning Engineer Internship, TRL - US Remote
Can you explain your experience with fine-tuning large language models for the Machine Learning Engineer Internship?

When answering this question, highlight specific experiences where you have worked with fine-tuning LLMs. Discuss the models you used, techniques applied, and results achieved. Sharing examples will illustrate your expertise and familiarity with the responsibilities of the role.

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What are your thoughts on the importance of open-source collaboration in machine learning?

Discuss how open-source collaboration fosters innovation and community engagement within ML. Emphasize your enthusiasm for contributing to projects, sharing insights, and how it leads to continuous improvement and learning for everyone involved.

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How do you ensure code quality and maintainability in your projects?

You should discuss strategies you implement to maintain code quality, such as writing clear documentation, conducting peer reviews, and utilizing version control systems like Git. Showcase your commitment to producing clean, maintainable code that supports future improvements.

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Describe your experience with Python and PyTorch in machine learning projects.

Detail your experiences working with Python and PyTorch, including specific projects, challenges faced, and how you overcame them. Illustrate your proficiency through examples of algorithms implemented or optimizations achieved.

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What experience do you have with community engagement in open-source projects?

Share instances where you have engaged with an open-source community, such as responding to issues, contributing to discussions, or writing documentation. Highlight the importance of feedback and community support in developing robust ML tools.

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How do you stay up-to-date with advancements in machine learning research?

Discuss the resources you utilize to stay informed, such as academic journals, online courses, and webinars. Highlight your approach to integrating new findings into practical implementations in your projects.

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What techniques are you familiar with regarding post-training methods for LLMs?

Describe your understanding of various post-training techniques, such as PPO or DPO. Discuss any experience you have implementing these methods and their significance in the development of language models.

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How would you rate your communication skills for sharing complex ML concepts?

Emphasize your communication skills, particularly your ability to simplify complex concepts for diverse audiences. Share examples of blog posts, tutorials, or presentations you’ve created that demonstrate this skill.

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Can you describe a project where you implemented distributed training?

Provide details about a project where distribution training was necessary. Discuss the challenges, the technologies utilized, and how you managed the distributed systems to achieve desired outcomes.

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Why do you want to work as a Machine Learning Engineer Intern at Hugging Face?

Be honest about your passion for machine learning and open-source innovation. Discuss Hugging Face's impact on the AI community and how you'd like to contribute to the mission and learn from the team.

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DATE POSTED
November 29, 2024

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