Research Scientist

🕒 August 31

🌐 United States, Australia – Remote

🇺🇸 United States – Remote 🇦🇺 Australia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧬 Research Scientist

👻 Ghost score 33%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Pluralis Research

WebsiteLinkedInAll Job Openings

1 - 10 employees

🤖 Artificial Intelligence

🌐 Web 3

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

• Identify and solve open problems blocking Protocol Learning at scale, including communication efficiency, convergence under churn and staleness, heterogeneity, and robustness to malicious participants • Publish research in Tier-1 venues • Collaborate with the engineering team to integrate research methods into live training runs • Advance decentralized training and serving of large models on consumer-grade devices over the internet • Conduct research toward scaling from the 8B run to frontier-scale models

🎯 Requirements

• PhD in machine learning with publications in top-tier conferences such as NeurIPS, ICML, or ICLR • Hands-on experience in large-scale distributed training and compression strategies • Strong programming ability in PyTorch • Belief that Protocol Learning is a viable path for collective, trustless, and sovereign AI • Experience with foundation model pre-training, post-training, or reinforcement learning is nice to have • Experience at proprietary, open-weight, or open-source AI labs is nice to have • Professional-level English proficiency, written and spoken • Comfortable working across time zones

🏖️ Benefits

• Significant equity ownership for key technical contributors in addition to a high base salary • Flexible remote work environment • Full visa sponsorship and relocation support to Australia or the US for exceptional candidates • Opportunity to work on open research problems and publish foundational papers • Globally distributed team • Exposure to frontier-scale model training and serving