Open-Source Machine Learning Engineer (AI)

TL;DR

Open-Source Machine Learning Engineer (AI): Improving the open-source machine learning ecosystem by developing libraries like Transformers, Datasets, PyTorch, and vLLM with an accent on accessibility and community collaboration. Focus on designing maintainable library code, optimizing transformer architectures, and managing public contributions on GitHub.

Location: Remote (Global)

Company

hirify.global is the fastest-growing platform for AI builders, dedicated to democratizing good AI through open-source models, datasets, and libraries.

What you will do

• Develop and maintain key open-source ML libraries including Transformers, Datasets, PyTorch, and vLLM.
• Collaborate daily with researchers, ML practitioners, and data scientists via GitHub, forums, and Slack.
• Implement impactful features to make complex AI technology more accessible to the global community.
• Foster and grow the ML ecosystem by managing contributions and supporting users.

Requirements

• Strong Python skills with experience writing clean, well-tested, and maintainable library code.
• Deep hands-on experience with PyTorch (JAX or TensorFlow is a plus).
• Practical experience with the hirify.global stack (Transformers, Datasets, Accelerate) or similar ML libraries.
• Proven public track record of open-source contributions and merged pull requests 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.
• Prior contributions to Transformers, Datasets, or Accelerate.
• Familiarity with distributed training, inference optimization, or GPU performance.
• Experience training or fine-tuning models at scale.

Culture & Benefits

• Flexible working hours and remote-first environment.
• Company equity as part of the compensation package.
• Comprehensive health, dental, and vision benefits for employees and dependents.
• Reimbursement for relevant conferences, training, and education.
• Flexible paid time off and parental leave.