MLOps

- Own inference infrastructure end-to-end: optimize latency, throughput, and cost across our model fleet. - Build and scale model serving with TensorZero, vLLM/SGlang/TRT, and Kubernetes. - Design and maintain vector search pipelines with Vector storages. - Familiarity with support metrics (SLAs, FCR, deflection) and ability to define service health KPIs. - Turn research into product: grab experimental models from the research team, figure out what's production-ready, and ship it - formatting, sampling parameters, deployment, the whole thing