Member of Technical Staff, GPU & Distributed Systems

Reactor is building an inference platform for real-time world models. The Member of Technical Staff will build and optimize distributed cloud systems for multi-node inference, model loading and distribution, GPU communication, scheduling, and reliable serving.

Responsibilities:

• Multi-node inference. Build distributed worker initialization, sharded model loading, and coordinated execution across GPUs and machines. Work with model engineers to make tensor, pipeline, and sequence parallelism perform well in production
• Fast model startup. Engineer parallel checkpoint loading, weight streaming, host-to-device transfers, and GPU snapshot/restore to cut cold starts from minutes to seconds
• Model distribution. Build transfer, caching, prefetching, and replication systems that move weights and large container images efficiently across clusters, regions, and clouds
• Scheduling and orchestration. Develop Kubernetes controllers, scheduling extensions, and placement algorithms that account for model residency, accelerator memory, interconnect topology, and session latency across AWS and GPU cloud providers
• GPU communication. Optimize collective operations and point-to-point transfers using NCCL, NVLink, and RDMA. Reduce synchronization overhead and overlap communication with computation
• Reliable, efficient serving. Build admission control, backpressure, and coordinated recovery from worker failures. Improve utilization across NVIDIA GPUs, AWS Trainium, and other accelerators
• You’ll build reproducible benchmarks, trace bottlenecks across the stack, and measure improvements in startup time, latency, throughput, and fleet utilization