Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI Engineer - up to £60,000

Stott & May Professional Search Limited
The City
1 year ago
Applications closed

Related Jobs

View all jobs

AI Engineer (Computer Vision)

AI Engineer - DV-Cleared, NLP & Speech Tech (Contract)

Senior AI Engineer — Remote NLP/OCR & Production Pipelines

Senior AI Engineer - NLP/LLM Systems (Hybrid London)

Senior AI Engineer — Health & Pharma NLP Lead

Data Engineer

AI Engineer (LLMs) London (Hybrid - 2 days a week in Central London Office( Salary: Up to £60,000 Up to 15% bonus We are currently working with a global professional services company that specialise in Public Relations. At present, they have a small AI functionality within their business services department who are developing in-house tools to automate internal processes. Due to increased demand, they are looking to grow this team and bring in an engineer to help design and build new tooling. This role will suit someone who has good experience of working in a similar environment but wants to be more creative as products and tools are built from the ground up (and not handed down by request). There is a lot of autonomy in this role and freedom to upskill across generative AI, particularly across Large Language Models. Key Responsibilities - Support and Iterate Existing AI Applications: Enhance the performance and utility of current AI applications. - Innovate and Develop New Solutions: Design, develop, deploy, and maintain scalable AI applications that drive operational and commercial success across various business use cases. - User-Centric Testing: Trial and test AI solutions with end users, iterating based on feedback to achieve optimal performance. - Data Research and Analysis: Utilize statistical and machine learning techniques to analyze data sets and inform AI development. - Stay Updated on AI Trends: Monitor the evolving AI landscape to ensure our solutions remain cutting-edge and relevant. Required Skills and Experience - Expertise in LLMs and Generative AI: 2 years experience in building solutions with Large Language Models and a good understanding of the generative AI landscape. - Python Proficiency: Strong experience in Python, including writing production-quality code. - Cloud Applications: Experience developing applications on Azure is great but other cloud platforms are also fine - Strong communication skills with an ability to engage with senior non-technical stakeholders Desirable Skills (but by no means mandatory) - DevOps: Familiarity with CI/CD and other DevOps practices. - Industry: Experience in professional services or similar field is beneficial. - Front-End Development: Familiarity with front-end languages such as JavaScript, React, HTML, and CSS is beneficial

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.