ML Research Engineer Internship, Post-Training - US Remote

The ML Research Engineer Internship at Hugging Face is an opportunity for aspiring engineers to work on cutting-edge post-training research for large language models. Interns engage in implementing state-of-the-art practices and contributing to impactful AI models within a diverse team dedicated to democratizing AI.

Anyone with a passion for open-source technology and a background in ML or deep learning can apply for the ML Research Engineer Internship at Hugging Face. We value diverse skill sets and experiences, so even if you don’t meet every requirement, we encourage you to submit your application.

Key skills for the ML Research Engineer Internship at Hugging Face include a strong foundation in machine learning, familiarity with large language models, coding experience, and a passion for research. Creativity and an eagerness to make complex technology accessible are also highly valued.

As an intern at Hugging Face, you will work on projects focused on improving the capabilities of large language models, including developing training regimes for reasoning and navigating complex environments. You'll also contribute to making these advancements accessible to the global AI community.

Interns at Hugging Face can expect a supportive and inclusive work culture that values diversity and encourages open dialogue. The company is committed to the well-being of its employees, offering flexible working hours and remote options to ensure everyone feels respected and supported.

Interns at Hugging Face have access to state-of-the-art equipment, including a large research cluster of H100s, a comprehensive training codebase, and guidance from experts in the field. Additionally, the company provides reimbursement for relevant conferences and educational opportunities.

Working on open-source projects at Hugging Face is important because it promotes collaboration within the AI community, democratizes access to advanced technologies, and fosters innovation. Hugging Face is dedicated to making complex AI models and tools available to everyone, enhancing global creativity and learning.

When answering this question, highlight any relevant projects you have worked on involving large language models. Discuss specific tasks you have performed, software you have used, and your understanding of model architectures, emphasizing your familiarity with training and fine-tuning processes.

Discuss your systematic approach to debugging, which may include analyzing error rates, using visualization tools, and adjusting model parameters. Provide examples from previous experiences where you've identified issues and implemented solutions, demonstrating your problem-solving skills.

When answering this question, select a project that showcases your initiative and ability to learn quickly. Explain the new technique, your rationale for its implementation, the challenges you faced, and the outcome. Emphasize what you learned from the experience.

List the programming languages you are skilled in—such as Python or Java—and highlight specific tools and libraries you have used, like TensorFlow, PyTorch, or Keras. Mention any relevant projects that demonstrate your proficiency in these technologies.

Articulate your passion for open-source AI and what drew you to Hugging Face specifically. Discuss the company’s mission and values, how you align with them, and what unique contributions you hope to bring to the team.

Provide a concise explanation of post-training within the context of large language models, touching on how it aims to refine models after initial training to enhance performance and adapt to specific tasks. Use examples like fine-tuning models for better reasoning capabilities.

Highlight your advocacy for user-centric design and your ability to translate complex ideas into digestible formats. Discuss strategies such as developing educational materials, tutorials, or visual aids that help bridge the gap between advanced technology and end-users.

Emphasize your commitment to continuous learning through resources like academic journals, online courses, and active participation in AI communities. Mention any influential figures or research papers that have shaped your understanding of current trends.

Choose a specific challenge related to a project that tests your critical thinking and resilience. Describe the context, how you addressed the challenge, and the lessons learned, showcasing your adaptability and growth mindset.

Discuss your time management strategies, such as using project management tools to create a schedule and set milestones. Emphasize your ability to adjust priorities based on project needs, maintaining quality without sacrificing deadlines.