The picture is cautious at the top line but hot in specific pockets. Through a subdued 2025 economy, businesses held back on general hiring while demand concentrated on specialist tech skills including AI, data, enterprise applications and cyber security Computer Weekly (tech recruitment outlook 2026). So the market isn't flat. It's uneven, and machine learning sits right in the busy part of it.
Demand for AI skills is the clearest signal. It rose by nearly 200% in a year, with London accounting for 80% of AI-related job postings and close to two-thirds of all UK technology vacancies The Register (Accenture data). Vacancy growth in the wider professional, scientific and technical sector backs this up: it saw the largest volume increase of any sector, up 5,000 in the three months to October 2025 ONS – Vacancies and jobs in the UK: November 2025.
That surge sits inside a labour market the Low Pay Commission describes as 'low hire, low fire', with weaker recruitment overall and vacancies below pre-pandemic levels Low Pay Commission Report 2025, GOV.UK. The takeaway for product teams: the talent you want is scarce and in demand, even while the broader market feels quiet.
The squeeze is heaviest at the junior end. UK tech cut graduate jobs by 46% in the past year, with a further 53% drop projected The Register. Entry-level postings have fallen sharply too, with a 30% drop since ChatGPT launched techUK – What's actually happening with entry-level and graduate jobs?. In engineering specifically, entry-level hiring has fallen to -19% against -10% for senior hiring, a nine-percentage-point gap GOV.UK - A snapshot of entry-level hiring in the UK.
That gap matters. It means the market is senior-weighted: teams are chasing experienced machine learning engineers who can ship, while fewer junior roles exist to build the next cohort. Employers are responding by growing their own. Apprenticeships have jumped from 3% of AI hires in 2020 to 19% in 2025 GOV.UK / DSIT – AI Labour Market Survey 2025 report.
Location adds another constraint. With London holding 80% of AI-related postings The Register (Accenture data), teams outside the capital lean harder on remote hiring and on the resident labour force. For the engineering profession, the vast majority of new hires already come from within the UK, a low reliance on international recruitment GOV.UK - Professionals in IT and engineering.
Start with a tight scope. A machine learning engineer in a product team is not a research scientist. Write the role around what the person will actually do: turn models into features, work with data pipelines, and ship reliably alongside product and engineering. A sharp scope shortens your shortlist and speeds every decision that follows.
Prioritise evidence over credentials. Ask for a model someone has taken to production and the trade-offs they made. With junior pipelines shrinking The Register, a degree filter narrows an already narrow field. Apprenticeship and self-taught routes are a growing share of AI hires GOV.UK / DSIT – AI Labour Market Survey 2025 report, so keep the door open to non-traditional backgrounds.
Then move fast. In a senior-weighted market where AI demand is up nearly 200% The Register (Accenture data), the best people hold several conversations at once. Compress your process: one practical exercise close to the real work, one team conversation, a clear decision. Slow, multi-stage loops lose good people to quicker teams.
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