Artificial Intelligence

AI has moved decisively from research to production, and the talent market has split in two. On one side is a flood of applicants with course certificates and prompt-engineering experience; on the other, a small pool of engineers who have actually shipped and operated production ML systems and LLM-powered features. The second group is scarce, expensive and almost never on the open market.

Demand is strongest for machine learning engineers with MLOps maturity, data scientists who pair statistical rigour with commercial judgement, and generative AI engineers who can take LLMs beyond demos into reliable, evaluated, cost-controlled products — particularly within the Microsoft ecosystem around Azure OpenAI and Copilot extensibility.

We recruit machine learning engineers, data scientists, MLOps and AI infrastructure engineers, generative AI and LLM specialists, AI product engineers and heads of AI/ML — for software product companies, consultancies and enterprises embedding AI into real operations across the UK, Europe, the USA and Australia.

In 2026, machine learning engineers typically earn £70,000–£110,000 in the UK, $150,000–$210,000 in the USA and AU$140,000–AU$190,000 in Australia, with staff and principal-level engineers well above those bands. Data scientists earn £55,000–£85,000 (UK) and $120,000–$170,000 (USA). Generative AI and LLM specialists typically command a 10–20% premium over these ranges.

In no other market is the gap between a plausible CV and genuine capability wider. Our consultants technically screen every AI candidate for shipped models, production MLOps experience and real LLM work — not coursework. Because we also recruit across cloud and data engineering, we understand the full stack an AI hire must fit into. We typically present a qualified shortlist within 3 to 5 working days.