Description
As an Open-Source Machine Learning Engineer, you'll work to improve the open-source machine learning ecosystem. You'll mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch, and vLLM, and you'll interact with users and contributors across the broad open-source ML ecosystem.
You'll need:
- Strong Python skills, with experience writing clean, well-tested, maintainable library code
- Deep hands-on experience with a modern deep-learning framework, especially PyTorch (JAX or TensorFlow a plus)
- Practical experience with the Hugging Face open-source stack (Transformers, Datasets, Accelerate) or comparable ML libraries
- A public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHub
- Solid understanding of modern machine learning and deep learning, including transformer architectures
- Experience collaborating with a technical community in the open (GitHub issues and reviews, forums, Slack or Discord)
- 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, Accelerate, or similar libraries
- Familiarity with distributed training, inference optimization, or GPU/accelerator performance work
- Experience training or fine-tuning models at scale
We offer:
- Flexible working hours and remote options
- Health, dental, and vision benefits for employees and their dependents
- Parental leave and flexible paid time off
- Company equity as part of your compensation package
- Reimbursement for relevant conferences, training, and education