Machine Learning Engineer, WebML - US Remote

Position Overview

• Location Type: Remote
• Employment Type: Full-time
• Salary: Not specified
• Description: Hugging Face is building the fastest growing platform for AI builders. This role focuses on expanding the Hugging Face ecosystem to web developers through the creation and maintenance of easy-to-use JavaScript/TypeScript machine learning libraries, specifically WebML. The goal is to bridge the gap between web development and machine learning by enabling models to run locally in the browser.

Requirements

• Open Source Community Management: Experience with issue tracking and pull request review.
• ONNX & Quantization: Experience with converting and optimizing models for in-browser inference.
• Web Technologies: Familiarity with tools like Optimum, Torch Dynamo, ONNXScript, and ONNXRuntime-GenAI.
• JavaScript/Web Experience: Experience building demo applications to showcase new features.
• WebGPU, WebNN, WASM: Understanding and experience with these technologies to enable running models in-browser at near-native speeds.
• JavaScript/TypeScript: Strong proficiency in JavaScript or TypeScript.

Responsibilities

• Contribute to the development and maintenance of JavaScript/TypeScript machine learning libraries (e.g., transformers.js, huggingface.js).
• Manage and contribute to the open-source community surrounding these libraries.
• Optimize models for in-browser inference using techniques like ONNX, quantization, and WebGPU/WebNN.
• Build and maintain demo applications to showcase the capabilities of WebML.
• Collaborate with other engineers and researchers at Hugging Face.

Application Instructions

• Encourage applicants to apply even if they don’t tick every box.
• Hugging Face values diversity, equity, and inclusivity and is an equal opportunity employer.

Company Information

• Company: Hugging Face
• Mission: Democratize good AI.
• Platform: Building the fastest growing platform for AI builders.
• Open Source Libraries: Includes transformers, diffusers, and datasets.
• Community: Over 5 million users & 100k organizations sharing over 1M models, 300k datasets, and 300k apps.
• Values: Diversity, Equity, and Inclusivity.