Research Engineer Intern
Pluralis Research is a research lab developing decentralized AI through Protocol Learning, a communication-efficient approach to collaborative model training. It operates open training systems that allow distributed contributors to provide compute for collectively owned foundation models.
Funding history
About Pluralis Research
Pluralis Research develops Protocol Learning, which enables foundation models to be trained and served across globally distributed participants without requiring a single participant to hold the complete model. Its work covers low-bandwidth model parallelism, asynchronous distributed optimization, fault-tolerant training, privacy-preserving unextractable models, and collective ownership. The organization operates Agora and Node0 training systems, publishes research, provides participation documentation, and releases open-source software for distributed training and reinforcement-learning workflows.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design, build, and ship a roadmap project for a production decentralized training system. You will improve multiprocessing, asynchronous I/O, and threading components, work with large-scale cloud training infrastructure, and contribute production code with regular review and mentorship.
Requirements
- Current enrollment in or recent completion of a Masters or PhD in machine learning, computer science, or a related field
- Strong Python and PyTorch skills
- Experience building concurrent or parallel systems
- Hands-on exposure to distributed machine learning
- Experience with AWS, GCP, or other hyperscalers
- Professional-level written and spoken English
Responsibilities
- Design, build, and ship a roadmap project
- Build and improve multiprocessing, asynchronous I/O, and threading components
- Work with large-scale training infrastructure across cloud providers
- Contribute to the production codebase daily
- Present the completed project to engineering and research teams