Description:

Hugging Face is seeking a Machine Learning Engineer for their WebML team, which focuses on bridging the gap between web development and machine learning.
The role involves maintaining and creating open-source machine learning libraries in JavaScript/TypeScript to make them accessible to web developers.
WebML enables models to run locally in the browser, allowing for low-latency, interactive, and privacy-focused web applications.
The position combines software engineering, machine learning, and open-source community building to expand the Hugging Face ecosystem.
Candidates will work on projects like transformers.js and huggingface.js to enhance the usability of machine learning in web applications.

Requirements:

Candidates should have experience in open-source community management, including issue tracking and PR review.
Knowledge of ONNX and quantization for converting and optimizing models for in-browser inference is required.
Familiarity with tools such as optimum, torch dynamo, onnxscript, and onnxruntime-genai is a plus.
Experience with web technologies like WebGPU, WebNN, and WASM to enable near-native model execution in the browser is necessary.
Proficiency in JavaScript and web development, including building demo applications to showcase new features, is essential.
Hugging Face encourages applications from diverse candidates, even if they do not meet every requirement.

Hugging Face promotes a culture of diversity, equity, and inclusivity, ensuring a respectful and supportive workplace for all employees.
The company values professional development, offering reimbursement for relevant conferences, training, and education.
Flexible working hours and remote work options are provided to support employee well-being.
Employees have the opportunity to visit office spaces located around the world, particularly in the US, Canada, and Europe.
The organization is committed to supporting the ML/AI community through collaboration and shared advancements in the field.