Hugging Face

Machine Learning Engineer, WebML - US Remote

New York, New York, United States

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, AI & Machine Learning, Web DevelopmentIndustries

Requirements

Candidates should possess experience in open source community management, including issue tracking and PR review, and demonstrate familiarity with ONNX, quantization, and tools such as optimum, torch dynamo, onnxscript, and onnxruntime-genai. Experience with web technologies like WebGPU, WebNN, and WASM is highly desirable, along with a strong foundation in JavaScript/web development, including the ability to build demo applications.

Responsibilities

The Machine Learning Engineer will focus on expanding the Hugging Face ecosystem to web developers through the creation and maintenance of easy-to-use JavaScript/TypeScript machine learning libraries, specifically transformers.js and huggingface.js, and bridging the gap between web development and machine learning. They will also contribute to the optimization and conversion of machine learning models for in-browser inference using techniques like ONNX and quantization, and explore and implement new web technologies such as WebGPU and WebNN to enable near-native model execution speeds within the browser.

Skills

JavaScript

TypeScript

WebGPU

WebNN

WASM

ONNX

Quantization

Optimum

Torch Dynamo

ONNXScript

ONNXRuntime-GenAI

Open Source Community Management

Hugging Face

Develops advanced NLP models for text tasks

About Hugging Face

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.

Key Metrics

New York City, New YorkHeadquarters

2016Year Founded

$384.9MTotal Funding

SERIES_DCompany Stage

Enterprise Software, AI & Machine LearningIndustries

201-500Employees

Benefits

Flexible Work Environment

Health Insurance

Unlimited PTO

Equity

Growth, Training, & Conferences

Generous Parental Leave

Risks

Salesforce's exclusive partnerships may limit Hugging Face's access to training datasets.

Microsoft's rStar-Math technique could outperform Hugging Face's NLP models in specific tasks.

DeepSeek-V3's release may intensify competition in the ultra-large model space.

Differentiation

Hugging Face offers a massive library of over one million AI models.

The company provides a thriving online community for open-source AI collaboration.

Hugging Face's freemium model allows easy access to advanced NLP tools.

Upsides

Collaboration with Microsoft could enhance small model performance in mathematical reasoning.

Partnership with DeepSeek may boost Hugging Face's ultra-large model capabilities.

Integration with Salesforce's ProVision could improve multimodal AI capabilities.

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