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As a Machine Learning Engineer, you'll design and implement distributed systems for training large-scale ML models while optimizing performance under challenging conditions.

The Research Scientist will tackle advanced research problems in Protocol Learning, publish findings, and work collaboratively in a distributed model training environment.

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

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

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.

Design and implement robust, large-scale distributed ML training systems optimized for low-bandwidth, high-latency environments. Build model-parallel training strategies, checkpointing and recovery, GPU and memory optimizations, P2P networking, NAT traversal, and monitoring to ensure resilient, efficient multi-participant training.