Internship

Machine Learning Engineer Internship

Trl

Confirmed live in the last 24 hours

Hugging Face

Hugging Face

201-500 employees

Develops advanced AI and NLP models

Enterprise Software
AI & Machine Learning

Remote in USA

Remote position with preference for candidates in France.

Category
Applied Machine Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Python
Git
Pytorch
Machine Learning

You match the following Hugging Face's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • Fine-tuning large language models (LLMs) or vision-language models (VLMs)
  • Proficiency in Python
  • Proficiency in PyTorch
  • Experience with frameworks like Hugging Face Transformers
  • Experience in distributed training and GPU acceleration
  • Familiarity with Git/GitHub workflows
  • Exposure to cutting-edge ML research
  • Experience in benchmarking and testing fine-tuning methods
  • Building tools to streamline workflows
  • Ensuring software stability, backward compatibility, and versioning
  • Writing blog posts and tutorials
  • Engaging with the community
Responsibilities
  • Collaborate with the research team to integrate cutting-edge methods into the library
  • Maintain a clean and scalable codebase
  • Ensure usability through thoughtful documentation
  • Engage with the TRL community by responding to issues and gathering feedback
  • Foster collaboration through thoughtful discussions and support
Desired Qualifications
  • Passion for open-source innovation
  • Interest in making advanced ML tools accessible globally
  • Willingness to learn and grow in a collaborative environment

Hugging Face develops machine learning models focused on understanding and generating human-like text. Their main products include advanced natural language processing (NLP) models like GPT-2 and XLNet, which can perform tasks such as text completion, translation, and summarization. Users can access these models through a web application and a repository, making it easy to integrate AI into various applications. Unlike many competitors, Hugging Face offers a freemium model, allowing users to access basic features for free while providing subscription plans for advanced functionalities. The company also tailors solutions for large organizations, including custom model training. Hugging Face aims to empower researchers, developers, and enterprises to utilize machine learning for text-related tasks.

Company Stage

Series D

Total Funding

$384.9M

Headquarters

New York City, New York

Founded

2016

Growth & Insights
Headcount

6 month growth

0%

1 year growth

1%

2 year growth

-2%
Simplify Jobs

Simplify's Take

What believers are saying

  • Recent SmolVLM models reduce computing costs, enhancing AI deployment on everyday devices.
  • Hugging Face's platform hosts cutting-edge models like DeepSeek's Janus Pro, boosting its reputation.
  • Open-sourcing advanced models aligns with industry trends, attracting more users and collaborators.

What critics are saying

  • DeepSeek's Janus Pro outperforms leading models, posing a competitive threat to Hugging Face.
  • DeepSeek's cost-effective R1 model pressures Hugging Face to innovate or lower prices.
  • Chinese AI companies' high-performing models challenge Hugging Face's open-source platform position.

What makes Hugging Face unique

  • Hugging Face offers state-of-the-art NLP models like GPT-2 and XLNet.
  • The company provides a freemium model with advanced features available via subscription.
  • Hugging Face's open-source platform attracts diverse clients, including researchers and developers.

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Benefits

Flexible Work Environment

Health Insurance

Unlimited PTO

Equity

Growth, Training, & Conferences

Generous Parental Leave