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
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 that can understand and generate human-like text, focusing on natural language processing (NLP). Their main products include models like GPT-2 and XLNet, which can perform various 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 different applications. Unlike many competitors, Hugging Face offers a freemium model, providing basic features for free while charging for advanced functionalities and enterprise solutions tailored to large organizations. The company's goal is to empower researchers, developers, and businesses to utilize AI for text-related tasks effectively.

Company Stage

Series D

Total Funding

$384.9M

Headquarters

New York City, New York

Founded

2016

Growth & Insights
Headcount

6 month growth

1%

1 year growth

2%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Integration of reasoning models could enhance Hugging Face's NLP capabilities.
  • Leveraging ProVision framework may improve Hugging Face's multimodal AI models.
  • Adopting rStar-Math could enhance mathematical reasoning in Hugging Face's models.

What critics are saying

  • MiniMax's LLM with 4M token context challenges Hugging Face's large context handling.
  • Google's Gemini AI may outpace Hugging Face in multi-modal AI capabilities.
  • Novasky's free AI model could undercut Hugging Face's pricing model.

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 collaborates with tech companies and academic institutions for revenue.

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Benefits

Flexible Work Environment

Health Insurance

Unlimited PTO

Equity

Growth, Training, & Conferences

Generous Parental Leave