Pluralis Research
San Francisco, California, United States +1
Own the inference stack: You build and own it end-to-end. Pipeline-parallel execution, placement and routing, the transport, the serving engine, and failure handling. You set the direction, and you make things happen.; Invent the algorithms: Making inference fast on consumer…
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Distributed pretraining: Implement and optimize model-parallel training. Data, pipeline, and tensor parallelism for large models on heterogeneous GPUs under low-bandwidth, high-latency links.; Performance optimization: Implement techniques that reduce communication overhead…
Pluralis Research · San Francisco, California, United States +1
Own the threat model: You enumerate what a malicious or careless worker can do across pre-training, post-training, and inference — training disruption and denial-of-service, free-riding, model poisoning and backdoors, data extraction from gradients and activations, reputation…
Pluralis Research · San Francisco, California, United States +1
Build the post-training stack: You build the RL training loop end-to-end: rollout ingestion from the geo-distributed inference pipeline, reward computation, policy updates, and getting updated weights back out to the network. You set the direction, and you make things happen.;…
Pluralis Research · San Francisco, California, United States +1
Multi-cloud infrastructure: Design the resource management systems that provision and orchestrate compute across AWS, GCP, and Azure with infrastructure-as-code (Pulumi/Terraform). Handle dynamic scaling, state synchronization, and concurrent operations across hundreds of…