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Pluralis Research invites established researchers for collaboration on decentralized AI through joint publications and shared insights, focusing on model-parallel training.

The Staff Frontend Engineer will develop and refine frontend systems for visualizing decentralized training environments, collaborate on UX design, and maintain high-performance web applications.

Conduct research in Protocol Learning, publish findings, and engage with distributed machine learning on consumer-grade devices. Transform ideas into foundational papers.

As a Machine Learning Engineer, you will implement and optimize decentralized training systems for AI models, focusing on distributed training, performance optimization, and deployment of sharded models.

The Research Scientist Intern will conduct novel research in Protocol Learning, aimed at publishing in top-tier machine learning conferences, and will gain mentorship from senior scientists.

The role involves optimizing P2P connections for high-performance, designing fault-tolerant systems, collaborating on open-source projects, implementing security practices, and improving system performance.

As a Senior Frontend Engineer, you will develop user-friendly, high-performance applications for decentralized model training, collaborating with cross-functional teams.