Internship

Machine Learning Engineer Internship

Quantization

Posted on 12/16/2024

Hugging Face

Hugging Face

201-500 employees

Develops advanced NLP models for text tasks

Enterprise Software
AI & Machine Learning

Remote in USA

Position is fully remote, can be done from France or any other location.

Category
Applied Machine Learning
AI & Machine Learning
Requirements
  • Passion for open-source
  • Interest in making complex technology accessible to engineers and artists
  • Ability to integrate new quantization methods in the Hugging Face ecosystem
  • Experience with software engineering and machine learning engineering
Responsibilities
  • Integrate new quantization methods in Hugging Face ecosystem (transformers, accelerate, peft, diffusers)
  • Maintain existing integration (bitsandbytes, awq, autogptq)
  • Ensure community awareness of these tools through benchmarks and blogposts
  • Drive forward quantization in the open source ecosystem

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, 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

26%

1 year growth

76%

2 year growth

124%
Simplify Jobs

Simplify's Take

What believers are saying

  • Trend towards smaller AI models could inspire Hugging Face to optimize efficiency.
  • Shutterstock's 'research license' model offers affordable access to high-quality datasets.
  • Open-source video generation models present expansion opportunities for Hugging Face.

What critics are saying

  • Smaller AI models like Microsoft's Phi-4 challenge Hugging Face's larger models.
  • Shutterstock's model lowers data access barriers, reducing Hugging Face's competitive edge.
  • Tencent's free AI video generator intensifies competition in video generation space.

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 for paid subscribers.
  • 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