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 specialise in developing software for IoT edge devices, cloud services, front-end 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 life-cycle.
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 optimise 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 organisational 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?
Please send a CV to
