Gain essential insights into the UK machine learning talent market with our H2 2025 report. This guide explores how the ML hiring landscape has evolved in the second half of the year, shaped by rapid Generative AI adoption, changing role expectations and intensifying competition for experienced talent.
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Machine Learning H2 2025 Talent Report
Guy Gabriel
11th Jan 2026
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Key Highlights
- Market Trends: Demand for machine learning talent in H2 2025 has been driven primarily by Generative AI and large language model adoption. The “AI Engineer” title has overtaken traditional ML Engineer and Data Scientist roles, reflecting a shift towards production-ready, product-focused AI teams. While banking and finance remain present, their dominance has declined as startups and AI-native companies lead hiring.
- Emerging Skills: Employers are increasingly seeking full-stack AI engineers who can work across model development, APIs, product integration and user-facing features. High demand continues for candidates with hands-on experience fine-tuning, deploying and evaluating LLMs, alongside strong software engineering fundamentals.
- Hiring Challenges: Competition for experienced ML and AI engineers remains intense, pushing salaries higher for scarce, impact-oriented skill sets. Clients with clear role definitions, streamlined interview processes and a strong value proposition are consistently more successful, particularly for senior and production-focused hires. At the same time, demand is growing for high-potential junior talent with strong academic backgrounds, quality internships or demonstrable project work.
- Future Outlook: Demand is expected to remain strong into 2026, fuelled by continued GenAI investment, AI-first startup growth and increasing emphasis on commercial impact. While flexibility still matters, a gradual return to hybrid and office-based working is emerging as collaboration, technical challenge and long-term growth take priority for candidates.