MLOps Engineers build the platform that lets ML/AI Engineers iterate quickly — feature stores, training infrastructure, model serving, experiment tracking, monitoring, and the CI/CD pipelines that connect them. The role overlaps with Platform / SRE / ML Engineering, with the ML-system lifecycle as the focused responsibility.
Salary by Experience Level
Junior
$110,000 – $145,000
per year
Mid-Level
$150,000 – $210,000
per year
Senior
$220,000 – $330,000
per year
Required Skills
KubernetesKubeflow / Ray / Argo WorkflowsFeature stores (Feast, Tecton)Model serving (Triton, vLLM, TorchServe)MLflow / Weights & BiasesGPU scheduling and fractional GPUsObservability (Prometheus, Grafana)Cost optimisation for training and inference