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Get Involved

NDIF is under continuous development, and there are several ways to get involved in the prototype fabric during its construction.

  • Join our community of early adopters. Our online discord server hosts students and researchers from many fields who are dissecting the behavior and mechanisms of large AI models. Request early access to the prototype NDIF service through this community.
  • Use our open-source library, nnsight. NNsight can be used with NDIF and it can also be used with your own local computation power, independently of the fabric. It works with pytorch and can be easily installed via pip.
  • Join our team. We are looking for talented and motivated team members who are inspired to create a vibrant scientific community to crack the mysteries of large-scale AI. Jobs and opportunities are listed on this page.

The NDIF project code is open-source and can be found at github.com/ndif-team.


An NDIF workshop for undergraduate and graduate students, introducing state-of-the-art methods for performing interventions on the internal computations of large language models, using NDIF. NDIF enables students and scientists to share GPU resources to learn, develop, and deploy scientific methods that crack open the internals of large neural networks

NDIF Community

On the NDIF community discord, you can chat with the team and discuss tips, tricks, and the latest research. Submit a short form to join.

Join the group
NNsight

You can use NDIF right away in local mode without an account by using the nnsight library. Just a "pip install" away. Read about it here.

Go to nnsight
Jobs

We are looking for help building NDIF. To join the NDIF team full-time, part-time, as a co-op or a volunteer, see our job listings on this page.

See jobs below

Jobs and Community Opportunities

We are seeking a dynamic and tech-savvy individual to join the National Deep Inference Fabric (NDIF) as the Technical Community Outreach & Education Manager to advance our cutting-edge nationally funded AI research platform around Large Language Models. As the face of our project, you will be instrumental in creating and nurturing a vibrant community of researchers. Your primary responsibilities include developing engaging content such as newsletters, articles, technical tutorials, and workshop material tailored to both technical and non-technical audiences. In addition to content creation, you will be responsible for organizing open-source efforts to create a website containing tutorials and online materials, and you will organize conferences and workshops at multiple locations to help foster adoption of the platform collaboration within the community.

The ideal candidate will have a strong ability to convey complex concepts in an accessible manner and will have a strong understanding of machine learning and AI including python and pytorch.

Your role will be pivotal in establishing NDIF as a leading hub for AI research in America. You will drive initiatives that enhance our community's engagement and position our group as a thought leader in the field. If you are passionate about technology, community building, and aspire to play a key role in shaping the future of AI research, we encourage you to apply.

This is a full-time role, based in Boston, MA.

Apply here

We are seeking a highly skilled Principal Research Software Engineer with experience in Machine Learning and Large Language Model interpretability research methods, to assist in developing the National Deep Inference Fabric, an open-source deep learning interpretability research computing infrastructure project.

You will be responsible for full stack development, doing both back-end and front-end software development to help create a robust, high-throughput, highly usable, and flexible multi-tenant AI inference service to enable research nationwide. Some of the day-to-day activities include solving security, stability, integration, and performance issues involved in providing a large-scale research inference service for open-source AI models.

We are looking for someone who can implement state-of-the-art parallel GPU inference methods, and incorporate them into a system with job scheduling, routing, quota management, authentication, authorization, and telemetry to create a high-performance computing infrastructure. This person should be expert in Python and working internals of PyTorch along with Unix/Linux service development, HPC/cloud environments, and all other aspects of the software development life cycle.

This is a full-time role, based in Boston, MA

Apply here.

The Summer 2024 NDIF Engineering Fellowship is an intensive program for systems- and ML-focused students to contribute to an active state-of-the-art AI research engineering project in the public interest. The program welcomes applicantions from PhD, Masters, and undergraduate students in computer science who have knowledge and interest in ML Systems.

More information on how to apply to the fellowship here.

In the future we will post specific listings for other roles we seek to fill including

  • Student research assistants.
  • Student co-ops.

We also welcome research collaborators and unpaid open-source contributors; for open-source community opportunities, get in touch through our community Discord.