Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries).
Implement and optimize open-source and internal libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches.
Collaborate with the open-source community (PyTorch, vLLM, Hugging Face).
Requirements
Master’s degree in Computer Science, Machine Learning, Data Science, or a related field
Experience contributing to popular open-source libraries such as PyTorch, Tensorflow, JAX, vLLM, Transformers, Llama.cpp, ...
Passion for contributing to the open-source software ecosystem
Expert programming skills in Python, PyTorch, MLOps
Adaptable, proactive, and autonomous
Attention to detail and a drive to go the last mile to build almost perfect tools
Deep understanding of machine learning approaches, especially LLMs and algorithms
Low-ego, collaborative and have a real team player mindset
Experience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization) - ideal
Experience working with Slurm - ideal
Worked with research teams before - ideal
Experience as a core-maintainer of a popular ML open-source library - ideal
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