Research Scientist – Decentralized Training and Inference Verification

🔥 21 hours ago

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧬 Research Scientist

👻 Ghost score 25%

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

• Enumerate and maintain the threat model for malicious or careless workers across pre-training, post-training, and inference • Account for training disruption, denial-of-service, free-riding, model poisoning, backdoors, data extraction, reputation manipulation, and reward manipulation • Build statistical verification methods with stated error rates • Tune verification tests using rigorous benchmarks • Control false positives and false negatives across heterogeneous hardware, including GPUs and Macs • Build and operate the verification service in the inference path • Take responsibility for the verifier's operational mistakes

🎯 Requirements

• Built a calibrated statistical decision system with stated error rates, either shipped or published • Deep expertise in statistics and probability • Ability to design experiments, calibrate decision thresholds, and defend claimed error rates • Knowledge of verification methods for untrusted compute, including statistical testing, re-execution, cryptographic proofs, and trusted hardware • Ability to evaluate verification approaches for a permissionless network • Belief in Protocol Learning as a viable approach for collective, trustless, and sovereign AI • Familiarity with large-scale pre-training and RL post-training • Familiarity with decentralized ML security and adversarial threat models, including poisoning, Sybil, collusion, and replay • Experience at proprietary, open-weight, or open-source AI labs • Professional-level English proficiency, written and spoken • Comfortable working across time zones

🏖️ Benefits

• Significant ownership/equity for key technical contributors • High base salary • Flexible work environment • Full visa sponsorship and relocation support to Australia or the US for exceptional candidates • Opportunity to work on open research problems and write first publications in the area