Research Scientist
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 identify and solve research questions affecting communication efficiency, convergence, churn, staleness, heterogeneity, and robustness. You will publish results in leading ML venues and work to put new methods into live training runs.
Requirements
- PhD in machine learning
- Publications in top-tier conferences including NeurIPS, ICML, or ICLR
- Hands-on experience in large-scale distributed training
- Experience with compression strategies
- Strong PyTorch programming skills
- Professional-level written and spoken English
Responsibilities
- Identify and solve open Protocol Learning research problems
- Publish research in tier-1 ML venues
- Work with engineering to deploy methods in live training runs
Benefits
- Significant ownership for key technical contributors
- Flexible remote work environment
- Optional visa sponsorship and relocation support to Australia or the US