Description:

Hugging Face is seeking a Machine Learning Engineer Intern to contribute to the development of the TRL library, which focuses on post-training techniques for large language models (LLMs).
The intern will collaborate with the research team to integrate cutting-edge methods into the library, maintain a clean and scalable codebase, and ensure usability through thoughtful documentation.
Responsibilities include engaging with the TRL community by responding to issues, gathering feedback, and fostering collaboration through discussions and support.
The intern's contributions will influence thousands of developers globally, advancing the adoption of state-of-the-art post-training techniques.
The role requires a passion for open-source innovation and a commitment to making advanced ML tools accessible.

Requirements:

Knowledge and experience in machine learning, specifically in fine-tuning large language models (LLMs) or vision-language models (VLMs), and optimization techniques.
Proficiency in software development, particularly in Python, PyTorch, and frameworks like Hugging Face Transformers, with experience in distributed training and GPU acceleration.
Familiarity with open-source practices, including Git/GitHub workflows, community engagement, documentation, and collaborative development.
Exposure to cutting-edge ML research, benchmarking, and testing fine-tuning methods.
Experience in building tools to streamline workflows, ensuring software stability, backward compatibility, versioning, and delivering reliable releases.
Strong communication skills for writing blog posts, tutorials, and sharing updates on platforms like LinkedIn to engage with the community.
A cover letter is required, detailing the applicant's interest in working in open-source at Hugging Face, along with skills, potential expertise, and topics of interest.

Hugging Face promotes a culture of diversity, equity, and inclusivity, ensuring a respectful and supportive workplace for all employees.
Employees have access to reimbursement for relevant conferences, training, and education to support their professional development.
The company offers flexible working hours and remote options, supporting employees regardless of their location.
Remote employees have the opportunity to visit office spaces around the world, and the company will outfit workstations to ensure success.
Hugging Face fosters a collaborative community that supports significant scientific advancements in the ML/AI field.