Machine learning and AI Engineer

FSP Retail Team
Glasgow
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist / Statistician (Model Developer)

Data Scientist / Statistician (Model Developer)

Data Scientist / Statistician (Model Developer)

Senior Data Engineer

Machine Learning Engineer

Senior Machine Learning Engineer

Role Overview

We are seeking a ML and AI Engineer to join our growing Data & AI team and play a pivotal role in designing and delivering next-generation Artificial Intelligence solutions, with a strong emphasis on Generative AI (GenAI) technologies, Agentic AI, and Large Language Models (LLMs), for our public sector and enterprise clients.

As a ML and AI Engineer, you will collaborate with data architects, engineers, and business stakeholders to create innovative, cloud-based AI solutions that leverage the latest advancements in GenAI. You’ll be instrumental in helping clients unlock new value from their data, automate complex processes, and drive digital transformation through the practical application of cutting-edge AI.

This is an exciting opportunity to join a passionate and forward-thinking team, working on impactful projects across diverse industries. You’ll help shape the future of AI adoption for our clients, delivering solutions that make a real difference.

Responsibilities
  • Fine-tune, deploy, and monitor Generative AI models and Agentic AI for enterprise use cases.
  • Develop and implement Retrieval-Augmented Generation (RAG) pipelines and advanced context engineering strategies.
  • Integrate Agentic AI into business workflows to accelerate solution delivery.
  • Collaborate with data engineers to bring Agentic capabilities to production.
  • Stay current with AI trends, tools, and best practices, and drive innovation within the team
About you
  • 3+ years of experience in ML/AI, with a recent focus on GenAI and LLMs.
  • Experience with GenAI frameworks (e.g., Hugging Face, LangChain, Agentic).
  • Proficient in context engineering, RAG, and LLMOps.
  • Experience deploying ML/AI solutions on Azure (Azure OpenAI, Azure AI Foundry).
  • Strong understanding of responsible AI and model safety.
  • Have experience in Computer Vision for Optical Character Recognition (OCR), and object recognition
What we look for in our people
  • Strong alignment with FSP values and ethos
  • Commitment to teamwork, quality and mutual success
  • Proactivity with an ability to operate with pace and energy
  • Strong communication and interpersonal skills
  • Dedication to excellence and quality
Who are FSP?

FSP Consulting Services (FSP) is a best-in-class digital transformation and cyber consultancy specialist combining real world experience in business strategy, change and adoption and digital solution delivery with a strong culture and social purpose. As a long-standing Microsoft Solutions Partner, our portfolio of modern workplace, cloud, data, and cyber security offerings, alongside trusted managed services delivery, is driving change for high-profile clients in both the public and private sector. Our work is founded on the commitment to deliver positive impact for both organisations and their people. As an employee-first organisation, FSP is committed to creating a culture of True Belonging, Excellence Everywhere, and Creating Opportunity. We are proud to have been recognised by Best Companies as a 3-star ‘World Class’ workplace (their highest level of accreditation) in 2024, 2023 and 2022. We were also awarded No.1 Best Company to Work For in the UK, in the Technology sector and in the South-East (Regional League Table) in 2023. We have also been recognised three times as No.1 Best Workplace in the UK by Great Place to Work. Find out more about our awards here: https://fsp.co/awards/

Why work for FSP?

At FSP, we are committed to providing:

  • A collaborative and supportive environment in which you can grow and develop your career
  • The tools and opportunity to do work you can be proud of
  • A chance to work alongside some of the best people in the industry, who always seek to share their knowledge and experience
  • Hybrid working – we empower you to make smart choices about when and where to work to achieve great results
  • Industry leading coaching and mentoring
  • Competitive salary and an excellent benefits package

Equal and Fair Opportunity

FSP is an equal opportunity employer and we welcome applications from all suitable candidates. We consider all applicants for employment regardless of age, disability, sexual orientation, gender identity, family or parental status, race, colour, nationality, ethnic or national origin, religion or belief.

Research suggests that applicants from underrepresented groups are less likely to apply for roles if they do not precisely meet requirements, or if they felt there were clear barriers as to who should apply. If you are excited about a potential role with us but are concerned that you may not be a perfect fit, please do apply, as you may be the ideal candidate for this role or for a different vacancy within FSP.

We endeavour to always provide fair opportunity for applicants to show-case themselves in the best way possible during any interviews or meetings. If you require any adjustments for a call or in-person meeting, please let us know


#J-18808-Ljbffr

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.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.