Open-Source Machine Learning Engineer (AI)

TL;DR

Open-Source Machine Learning Engineer (AI): Improving the open-source machine learning ecosystem by developing and optimizing libraries like Transformers and vLLM with an accent on maintainable library code and community collaboration. Focus on expanding the accessibility of complex ML technology, optimizing inference, and fostering a global contributor community.

Location: Remote (Global). The company has office spaces in New York and Paris, and supports employees wherever they are.

Company

A leading platform for AI builders dedicated to democratizing good AI through open-source libraries and community-driven development.

What you will do

• Improve and maintain core open-source libraries such as Transformers, Datasets, PyTorch, and vLLM.
• Collaborate with a global community of researchers, ML practitioners, and data scientists via GitHub, forums, and Slack.
• Design and implement impactful features to make complex machine learning technology more accessible.
• Foster one of the most active ML communities by assisting users and contributors in utilizing and improving the tools.

Requirements

• Strong Python skills with experience writing clean, well-tested, and maintainable library code.
• Deep hands-on experience with PyTorch (experience with JAX or TensorFlow is a plus).
• Practical experience with the hirify.global open-source stack (Transformers, Datasets, Accelerate) or similar ML libraries.
• A public track record of open-source contributions (merged pull requests to ML or data libraries) on GitHub.
• Solid understanding of modern deep learning and transformer architectures.
• Fluent written English for asynchronous collaboration across a distributed, global community.

Nice to have

• Experience maintaining an open-source project.
• Familiarity with distributed training, inference optimization, or GPU/accelerator performance work.
• Experience training or fine-tuning models at scale.

Culture & Benefits

• Remote-first environment with flexible working hours.
• Comprehensive health, dental, and vision benefits for employees and their dependents.
• Company equity provided as part of the compensation package.
• Reimbursement for relevant conferences, training, and education.
• Flexible paid time off and parental leave.
• Workstation equipment provided to ensure success in a remote setup.