Computer Vision Engineer

Role: Experienced AI /Machine Learning Engineer for computer vision

Location: Glasgow

Onsite: 2-3 days a week

Seeking £55,000 - £60,000 but negotiable

• PhD candidate with 1-2 years +
• Masters Candidate with 3-4 years +

We are looking for someone who has experience in computer vision, camera calibration, detection, segmentation and pose models. Also, on the data analysis and deployments of ML models.

As Machine Learning Engineer, you design, train and deploy the computer vision and machine learning models behind products like turning camera and sensor data into the accurate, trusted insights our customers rely on.

You report to the Lead of ML & AI and work closely with the Head of Hardware/Devices on camera and sensor requirements, and the Head of Software on integrating models into production systems.

You’ll work across the full ML lifecycle, from data and feature engineering through model training, evaluation and production deployment, with direct visibility across a small, collaborative team.

• Design, develop and deploy high-performing machine learning models for computer vision applications — image classification, object detection, segmentation and video analysis.
• Carry out data analysis, feature engineering and model selection to optimise model performance and accuracy.
• Develop and maintain robust, scalable ML pipelines using cloud services (e.g. AWS Sage Maker, EC2, S3, Lambda, Rekognition, MLFlow).
• Collaborate with data engineers, software engineers and product managers to translate business requirements into technical specifications.
• Stay abreast of advances in computer vision and machine learning research, and identify opportunities to apply them.
• Contribute to the development of machine learning infrastructure and best practice.
• Mentor junior team members and contribute to a culture of learning within the team.

• A Master’s or PhD in Computer Science, Computer Engineering or a related field, with a strong focus on machine learning.
• Solid understanding of deep learning concepts and architectures (CNNs, RNNs, Transformers) and their practical application.
• Proficiency in Python and common ML libraries (Tensor Flow, PyTorch, scikit-learn).
• Strong experience with AWS services (Sage Maker, EC2, S3, Lambda or equivalent).
• Experience with cloud-native development and deployment methodologies.

• Knowledge or experience in the aquaculture sector.
• Knowledge of MLOps principles and best practice.
• Experience with distributed computing and large-scale data processing.
• Experience with underwater or low-visibility imaging, or animal detection/tracking.

• A strong problem-solver, comfortable working with noisy, real-world data.
• Self-starting, able to work independently and as part of a small team.
• A strong communicator, able to explain model capability and limitations to non-technical stakeholders.
• Passionate about machine learning, with a desire to keep learning and growing.

This is a chance to build the computer vision and machine learning models behind a category-defining aquaculture technology platform — with direct visibility across a small team and models that go straight into products customers rely on.

• Competitive salary, based on experience
• 30 days annual leave (including bank holidays)
• Death in service at 4 x your annual salary
• Employee Assistance Programme
• Enhanced parental leave policies
• Birthday day off
• Paid bereavement and sick leave
• Company salary sacrifice pension scheme
• Cycle to work scheme
• Regular social breakfasts, lunches and team events