Pluralis Research works on Protocol Learning — decentralized, communication-efficient model-parallel training for foundation models. Backed by USV.
About the role
Publish in Tier-1 venues : Conduct novel research in Protocol Learning with the explicit goal of publishing in tier-1 ML conferences (NeurIPS, ICML, ICLR). Own a real problem : Pick a question that blocks Protocol Learning at scale and answer it — the internship is scoped so a foundational paper is a realistic outcome, not a stretch goal.
What they're looking for
- Publication track record (required) : Current PhD candidate with at least one publication in top-tier ML venues (NeurIPS, ICML, ICLR)
- Research focus : You work in a core technical area relevant to frontier models
- Technical depth : Strong theoretical understanding of deep learning and distributed systems principles
- Implementation skills : Proficiency in PyTorch and experience with large-scale training infrastructure
- Mission alignment : You believe Protocol Learning is the viable third path for collective, trustless, and sovereign AI
More about this role
Pluralis Research works on Protocol Learning: training and serving large models in a fully decentralized way on small consumer-grade devices connected via the internet. Despite being dismissed as infeasible, we have made significant advances on this problem, most recently Agora, a permissionless run that pretrained an 8B model from scratch on consumer GPUs spread over the internet, with no single participant ever holding the full weights ( tech report ). While many of the core research problems have been solved, Protocol Learning unlocks a series of new challenges. For the mission in full, read A Third Path: Protocol Learning .
This setting breaks nearly every assumption of datacenter training and inference: communication-efficient training across different parallelism axes, fault tolerance as nodes join and drop mid-run, heterogeneous compute and networks, and robustness to malicious participants. Our published methods include Subspace Networks , Factored Gossip DiLoCo , AsyncMesh , and Sentinel .
As a Research Scientist Intern you join us for a 6-month, fixed-term research internship during your PhD, focused on publishing. You work on the problems that stay open as we push from...
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