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The National Deep Inference Fabric (NDIF) is offering Summer Engineering Fellowships aimed at participating in a crucial summer initiative to enhance and rapidly expand AI research infrastructure, addressing the significant growth in state-of-the-art AI technologies.
NDIF is a project funded by the NSF, dedicated to developing a pioneering, highly-transparent large-scale AI inference infrastructure that facilitates scientific exploration on the largest open AI models.
This summer, the project is set to embark on an accelerated initiative to implement:
- High-throughput parallelism for a uniquely transparent large-scale LLM inference service.
- Service autodeployment for public scientific use on NCSA HPC GPU clusters.
- Robustness and monitoring to ensure reliable service for research users.
As we anticipate the emergence of open LLM models that will be significantly larger than current standards, the need for scientific infrastructure to support research at that scale is becoming increasingly urgent.
Fellowship OverviewThe NDIF Summer Engineering Fellowship is an intensive program designed for students focused on systems and machine learning, allowing them to contribute to a cutting-edge AI research engineering project that serves the public interest.
During the fellowship, participants will collaborate under the guidance of a team of distinguished professors specializing in machine learning and software engineering systems.
Your contributions will be vital in scaling the innovative NDIF inference infrastructure, laying the groundwork for enabling interpretability, safety auditing, and transparent research at a scale that aligns with the rapid advancements in AI model complexity.
Eligibility CriteriaThe NDIF engineering fellowship welcomes applications from current and recent PhD, Masters, and Undergraduate students in computer science and related disciplines.
The ideal candidate will possess knowledge of machine learning systems, including quantized and low-precision machine learning, ML compilers, and architectures designed for low-latency transformer inference. Both systems-focused and machine-learning-focused candidates will be considered.
Applicants must be at least 18 years old by the start of the fellowship.
Application ProcessTo apply, please submit your contact information, CV, current transcript, and a statement detailing your interest and potential contributions to the project through the designated application form.
Additional InformationNortheastern University values diversity and is committed to creating an inclusive environment for all faculty and staff. We encourage applications from individuals of diverse backgrounds and experiences.
Northeastern offers a comprehensive benefits package for eligible employees, which includes medical, vision, dental, paid time off, tuition assistance, wellness and life programs, retirement plans, and commuting support.
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