Pluralis Research
Artificial Intelligence • Web 3
Pluralis Research is a foundational AI research lab focused on Protocol Learning — decentralized, multi‑participant training of foundation models where no single participant holds a full copy of the model. The group develops methods to enable communication‑efficient model and pipeline parallelism, unextractable collaborative models, and high‑compression context parallelism so community‑trained, community‑owned frontier models can scale over low‑bandwidth, internet‑connected devices. Their work targets practical systems and algorithms that make decentralized training competitive with centralized training while enabling new ownership and economic models.
Research Engineer – Early-Career
Job not on LinkedIn
October 23
Pluralis Research
Artificial Intelligence • Web 3
Pluralis Research is a foundational AI research lab focused on Protocol Learning — decentralized, multi‑participant training of foundation models where no single participant holds a full copy of the model. The group develops methods to enable communication‑efficient model and pipeline parallelism, unextractable collaborative models, and high‑compression context parallelism so community‑trained, community‑owned frontier models can scale over low‑bandwidth, internet‑connected devices. Their work targets practical systems and algorithms that make decentralized training competitive with centralized training while enabling new ownership and economic models.
📋 Description
• Work directly with Pluralis Research Scientists and Machine Learning Engineers on core systems work • Run and monitor large-scale ML training (10B+ parameters) • Build infrastructure and experiment scaffolding • Handle data engineering and varied tasks for efficient research loop
🎯 Requirements
• Strong CS/math/EE fundamentals (e.g. first-class honours or equivalent) • Evidence of initiative: personal ML projects, hobbyist experiments, public repos, or other non-traditional work artifacts • High energy, self-directed, with strong learning velocity • University Medal or equivalent academic achievement • Experience or internships at high-performance environments (quant firms, top-tier tech) • Active presence in ML communities (Discord, X, open-source, etc.) • Demonstrated ability to take projects from idea to working artifact independently
🏖️ Benefits
• Support and scale infrastructure for large ML training and research • Build tools and automations to reduce operational load on scientists • Take on varied engineering tasks across the stack as needed • Learn quickly, ship frequently, and grow into a core engineering contributor
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