Top Tech Jobs & Startup Jobs in Melbourne

Build and optimize decentralized distributed pretraining systems for frontier-scale models on heterogeneous consumer hardware. Responsibilities include model-parallel training, communication efficiency, elasticity, fault tolerance, checkpointing, state synchronization, recovery, and monitoring across unreliable internet-connected devices. The role requires hands-on PyTorch distributed training experience, strong production Python skills, concurrency and profiling expertise, and evidence of shipping research or engineering systems.

Develop threat models, statistical verification algorithms, calibrated tests, and production verification services for decentralized training and inference on untrusted heterogeneous hardware. The role focuses on detecting incorrect model outputs, malicious training behavior, free-riding, poisoning, data extraction, and reward manipulation while controlling false positives and negatives. Candidates need deep statistics and probability expertise, experience shipping or publishing calibrated decision systems, and familiarity with statistical testing, re-execution, cryptographic proofs, and trusted hardware.