Internship

Machine Learning Engineer Internship

Accelerate

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

Category
Applied Machine Learning
Deep Learning
AI & Machine Learning
Requirements
  • Passion for open-source
  • Creativity and an eye for art
  • Desire to make complex technology accessible to engineers and artists
Responsibilities
  • Work at the intersections of software engineering, machine learning engineering, and education
  • Focus on distributed training through the accelerate library
  • Bring state-of-the-art training techniques into the library
  • Document and help teach others how distributed training techniques work
  • Touch on all aspects of distributed training and core library contributions
  • Engage in large-scale distributed training
  • Participate in API design
  • Write educational material aimed at a semi-technical audience
  • Understand the nuances of writing software that scales

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

28%

1 year growth

80%

2 year growth

128%
Simplify Jobs

Simplify's Take

What believers are saying

  • Test-time scaling allows smaller models to outperform larger ones in specific tasks.
  • FineMath dataset enhances AI capabilities in mathematical reasoning and problem-solving.
  • Growing demand for small AI models aligns with Hugging Face's democratization goals.

What critics are saying

  • SLMs challenge Hugging Face's focus on LLMs due to their efficiency and accuracy.
  • Patronus AI's Glider model offers cost-effective, detailed AI evaluations, posing competition.
  • Cohere's Command R7B model appeals to enterprises seeking fast, efficient AI solutions.

What makes Hugging Face unique

  • Hugging Face specializes in advanced NLP models like GPT-2 and XLNet.
  • The company offers a freemium model with enterprise solutions for custom AI needs.
  • Hugging Face collaborates on interdisciplinary projects, like LeMaterial for materials science.

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Benefits

Flexible Work Environment

Health Insurance

Unlimited PTO

Equity

Growth, Training, & Conferences

Generous Parental Leave