Inference & Model Serving across modalities (text, voice, code, vision)
Build and operate multi-model hosting on shared infrastructure
Own the model lifecycle: download, deploy, serve, monitor, update
Drive inference optimization: latency, throughput, cost; quantization, batching, caching
Ensure inference is fast and reliable for agents and systems
Platform & Technical Leadership: runtime, orchestration, tooling for autonomous agents

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