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 / Machine Learning Engineer

AI Engineer Machine Learning LLM - Polish Speaking

AI Platform Engineer (DevOps / MLOps Focus)

Senior MLOps Engineer

Machine Learning Engineer (Manager)

Machine Learning Engineer III

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.