Demand for machine learning skills is climbing fast, and the numbers are hard to ignore. Demand for AI skills rose nearly 200 percent in a year, with London accounting for 80 percent of AI-related job postings and nearly two-thirds of all technology vacancies in the UK according to Accenture data reported by The Register. That concentration tells you something: the talent market is tight, and employers who move quickly win the people who can do the work.
The pipeline is also changing shape. Apprenticeships have risen from 3% of AI hires in 2020 to 19% in 2025 in the GOV.UK AI Labour Market Survey 2025 report. For engineering leaders, that's an opportunity. You can grow evaluation and machine learning skills in-house, not just compete for a small pool of ready-made specialists.
Evaluation design has quietly moved from a nice-to-have to a named part of the brief. Building a model is only half the job. The other half is proving it behaves: measuring accuracy, catching drift, testing for bias and setting the benchmarks a team trusts before anything ships. Engineering teams now want people who can design that measurement layer as carefully as they design the model itself.
The scale of future demand backs this up. For the total of AI-related occupations, the net change ranges from approximately 696,000 jobs in the Automation Scenario to 1,072,000 in the Technological Opportunities Scenario, with replacement demand rising from 3,077,000 to 3,193,000 jobs across these scenarios in the GOV.UK AI Skills for Life and Work projections. Roles like machine learning engineer, MLOps specialist and evaluation lead sit right in the middle of that growth.
Start with the brief, not the job title. Write down what the model has to prove and who signs off that it works. If evaluation matters to you, say so in the first line of the advert and test for it in interview: ask people how they'd measure a model's performance, catch a regression or decide something is ready to ship.
Then widen the pool. Skills shortages remain real in adjacent fields: 70% of cyber firms reported at least one hard-to-fill vacancy in the AI Labour Market Survey 2025 report by Gardiner & Theobald. Hiring purely for a perfect CV match narrows your options. Instead, look for people who can reason about measurement and trade-offs, and lean on apprenticeships and internal training to build the rest. Move fast once you find the right person, because the strongest people don't stay available for long.
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