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Key Responsibilities:

  • Own the threat model: enumerate what malicious or careless workers can do across pre-training, post-training, and inference.
  • Design and calibrate statistical tests with stated error rates, tuned via rigorous benchmarks.
  • Ship the verifier: build and run the verification service in the inference path and live with its mistakes.

What We're Looking For:

  • Shipped or published verification systems with calibrated statistical decision making.
  • Deep statistical depth to design experiments and defend error rates.
  • Technical knowledge of verifying untrusted compute, from statistical testing to cryptographic proofs and trusted hardware.

Nice to Have:

  • Familiarity with large-scale pre-training and RL post-training.
  • Familiarity with decentralized ML security and adversarial threat models.
  • Experience at proprietary, open-weight, or open-source AI labs.

Compensation & Benefits:

  • Equity-heavy package with significant ownership for key technical contributors.
  • Remote-first culture with flexible work across global timezones.
  • Optional full visa sponsorship and relocation support to Australia or the US.

Pluralis Research

Pluralis Research is building Protocol Learning, a decentralized approach to training and serving large models on consumer-grade devices. They are a small, world-class team of ML researchers backed by Union Square Ventures, with a remote-first culture and an ideological commitment to trustless, sovereign AI.

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