Organisations increasingly need people who can move beyond a notebook: define an ML objective, prepare governed data, evaluate models, deploy inference, monitor behaviour and manage retraining. Generative AI adds new demand, but it also raises expectations around evaluation, safety, latency, cost and observability.
Salary depends on software-engineering strength, statistics and ML depth, production experience, platform ownership, industry and location. Treat market averages as dated directional evidence, never a guaranteed personal outcome. A stronger portfolio shows evaluation choices, deployment architecture, monitoring signals and limitations rather than only model accuracy.
