Research Scientist – Decentralized Training and Inference Verification

Pluralis Research

. Enumerate and maintain the threat model for malicious or careless workers across pre-training, post-training, and inference .

Posted 10/14/2026full-timeRemote • California • United States, AustraliaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in statistics and probability, with the ability to design experiments and calibrate decision thresholds. Proficient in verifying untrusted compute and familiar with decentralized ML security and adversarial threat models.

Highest-signal resume keywords

Statistical Decision System DevelopmentStatistical Testing and VerificationDecentralized ML SecurityAdversarial Threat Model AssessmentProfessional-Level English Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

StatisticsProbabilityExperiment DesignDecision Threshold CalibrationStatistical Verification MethodsError Rate AssessmentVerification of Untrusted ComputeCryptographic ProofsLarge-Scale Pre-TrainingReinforcement Learning Post-Training

Industry Keywords

Threat ModelTraining DisruptionModel PoisoningData ExtractionReputation ManipulationReward ManipulationPermissionless NetworkProtocol LearningHeterogeneous HardwareAI Labs

About the role

Key responsibilities & impact

Enumerate and maintain the threat model for malicious or careless workers across pre-training, post-training, and inference
Assess 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 different GPUs and Macs
Build and operate the verification service in the inference path
Verify that tokens came from the claimed model and sampling parameters
Verify that training contributions are what they claim to be

Requirements

What you’ll need

Built a calibrated statistical decision system with stated error rates and lived with its mistakes
Deep expertise in statistics and probability
Ability to design experiments, calibrate decision thresholds, and defend claimed error rates
Knowledge of verifying untrusted compute, including statistical testing, re-execution, cryptographic proofs, and trusted hardware
Ability to assess what verification approaches fit a permissionless network
Belief in Protocol Learning as a viable third path 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, and open-source AI labs
Professional-level English proficiency, written and spoken

Benefits

Comp & perks

Significant equity for key technical contributors in addition to a high base salary
Flexible work environment with team members distributed globally
Optional full visa sponsorship and relocation support to either Australia or the US