National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

AI/ML Engineer

Experis
5 months ago
Applications closed

Related Jobs

View all jobs

AI Engineer - Generative AI - £60,000 - Remote

Senior AI/ML Engineer (Data Science & Software Focus) [Urgent Search]...

Machine Learning Engineer | Ml Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Location: Scotland Job Type: Permanent Industry: Engineering Job reference: 99999_1737540727 Posted: about 5 hours ago

Role: AI/ML Engineer

Location: Glasgow OR Dundee

Salary: £70,000 max

Remote work:

This is a hybrid role and lots of our software team are Glasgow based and only come to the office a few times per month. We are looking at opening a hub in Glasgow as we know there is more talent there, so we would want them ideally working from the central Glasgow hub for 1-3 days per week and Dundee very occasionally.

The company:

We design and develop across a full stack of disciplines - Mechanical, Electronic, Electrical, and Software Engineering. Within our Digital team, we specialize in developing software for IoT edge devices, cloud services, frontend UI, AI/ML models in computer vision, and data analysis.

We take pride in fostering a collaborative and supportive work environment with a focus on both individual and team development.

Role Description and Purpose

We are seeking a talented and enthusiastic AI/ML Engineer to join our dynamic team at an exciting stage of our digital journey. As a mid-sized enterprise, you'll have the opportunity to work closely with colleagues across the business, gaining visibility and recognition for your contributions. If you thrive in a collaborative environment and enjoy making an impact, this role is for you.

As an AI/ML Engineer, you'll work alongside experienced professionals and gain hands-on experience throughout the entire product development lifecycle.

Responsibilities

Design, develop, and deploy high-performing machine learning models for computer vision applications, such as image classification, object detection, image segmentation, and video analysis. Conduct data analysis, feature engineering, and model selection to optimize performance and accuracy. Collaborate with cross-functional teams (e.g., data scientists, software engineers, and product managers) to translate business requirements into technical solutions. Develop and maintain robust, scalable machine learning pipelines using cloud services (e.g., AWS SageMaker, EC2, S3, Lambda) and other relevant technologies. Stay updated on advancements in computer vision and machine learning research, exploring new opportunities to apply these innovations to our projects. Contribute to the development and improvement of machine learning infrastructure and best practices. Mentor junior team members and promote a culture of innovation and continuous learning.

Experience & Skills

Master's or Ph.D. in Computer Science, Computer Engineering, or a related field, with a strong focus on machine learning. 3+ years of professional experience in developing and deploying machine learning models, particularly for computer vision applications. Strong understanding of deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications. Proficiency in Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn). Experience with cloud services, including AWS SageMaker, EC2, S3, Lambda, etc. Familiarity with cloud-native development and deployment practices. Ability to work independently as well as collaboratively. A strong passion for machine learning and a commitment to continuous growth.

General Skills

Excellent problem-solving abilities and creative thinking. Passion for learning and staying current with industry trends and best practices. Strong communication and teamwork skills, with openness and transparency as default. Initiative and a proactive approach to tasks. Flexibility and a focus on contributing to organizational success.

Bonus Points

Knowledge of MLOps principles and best practices. Experience with distributed computing and large-scale data processing. Familiarity with industry-specific applications of computer vision or machine learning.

Benefits:

37.5 hours working week 33 days annual leave Death in service at 4 x your annual salary Employee Assistance Programme Enhanced parental leave policies Birthday day off Paid bereavement leave Paid sick leave Company pension scheme Cycle to work scheme

How to apply?

People Source Consulting Ltd is acting as an Employment Agency in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas.

National AI Awards 2025

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 to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.