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

Apply Now

AI/ML Engineer

Experis
8 months ago
Applications closed

Related Jobs

View all jobs

Artificial Intelligence Engineer

Data Scientist or AI/ML Engineer

Data Scientist or AI/ML Engineer

Staff Machine Learning Engineer (UK)

Machine Learning Engineer

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.

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.