AI Performance Optimization Engineer

This in-house role focuses on maximizing throughput, minimizing latency, and reducing costs for large neural network systems across training and inference workloads. The engineer will optimize from low-level kernel tuning to distributed system configuration, utilizing advanced techniques like quantization, sparsity, and compiler-level improvements. Collaboration with cross-functional teams is key to translating research advances into production-ready, efficient AI solutions.