Senior Computer Vision Engineer

at  Wheelright

Job Advert
This is an exceptional opportunity for a PhD-qualified expert to lead the design and development of cutting-edge computer vision algorithms and optical systems for vehicle and tyre condition assessment. The role spans image processing, 2D and 3D analysis, and advanced machine learning techniques, including neural networks and deep learning.
The successful candidate will play a pivotal role leading the expanding Computer Vision team to develop the next generation of WheelRight products. They will be involve in developing, refining and scaling our image recognition algorithms for commercial applications, whilst also contributing to the AI strategy for WheelRight’s future products and services.
WheelRight is at the forefront of innovation providing tyre and vehicle inspection systems for the global automotive industry, addressing the critical need for automated fleet vehicle inspection. Our advanced technology automates the measurement of tyre pressure, tread depth, damage detection and sidewall analysis without the need for sensors on vehicles. This groundbreaking system is already being deployed across multiple regions, including the UK, Africa, Asia, and the Americas, working in partnership with leading global tyre manufacturers, fuel forecourt operators, and logistics fleet managers. Computer vision is an integral part of WheelRight’s product offering and with an increased focus on machine vision and AI based products WheelRight are now seeking a highly skilled and innovative Senior Computer Vision Engineer with a PhD in a relevant field to help shape the future of our AI and computer vision products.

ESSENTIAL REQUIREMENTS

• PhD in Computer Vision, Machine Learning or associated subject.
• Strong expertise in Python, with extensive experience using OpenCV, NumPy, and deep learning frameworks such as TensorFlow or PyTorch.
• Proven knowledge in Image Recognition, Object Detection, Semantic Segmentation, and sequential models (e.g., RNN, LSTM, Transformer).
• Experience with advanced object detection models such as YOLO, Faster RCNN, and SSD.
• At least 2 years post-doctoral research or industry experience in computer vision, specifically related to 2D and 3D imaging.
• Experience applying computer vision and machine learning solutions to real-world applications.

DESIRABLE SKILLS

• Knowledge of 3D sensing and reconstruction techniques from 2D images.
• Familiarity with C++ or C# for implementing algorithms, particularly using libraries like OpenCV.
• Experience with industrial cameras and hardware integration.
• Proficiency with version control systems (GIT, SVN, etc.).

• Design, develop, and optimise advanced image recognition algorithms for tyre condition measurement using cutting-edge image processing and deep learning techniques.
• Lead the development of optical systems for 2D and 3D image processing applications.
• Drive improvements in existing machine learning models, utilising WheelRight’s extensive annotated image datasets to enhance performance, functionality, and reliability.
• Apply computer vision and machine learning (including neural networks and sequential models) to solve real-world challenges in vehicle and tyre inspection.
• Collaborate with cross-functional teams to define product development strategies and explore new technological solutions.
• Contribute to the implementation of AI and computer vision strategies for WheelRight’s next-generation products.