- 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.
- 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.