2 of 2 vLLM Jobs in the South East

strongly preferred) Running ML workloads on Kubernetes - GPU scheduling, capacity, and cost management Model serving and inference at production scale (eg KServe, RayServe, Triton, vLLM, or similar) with real latency and cost constraints(preferred RayServe) MLOps pipeline tooling - training pipelines, model registries, feature stores, and lineage (Kubeflow, MLflow, Feast, Weights ...

PyTorch in particular) Practical experience with model deployment workflows - loading, format conversion, quantisation, or framework integration Comfortable working with inference serving stacks (for example vLLM, TensorRT‐LLM, or similar) Familiarity with Linux, containerisation (Docker), and cluster environments Comfortable in a customer‐facing role, able to communicate clearly with ...