Vision Scientist, Imaging Algorithm Engineer, CV/AI Developer

Collect and label imagery, develop detection and segmentation models, optimise inference on edge devices, and evaluate performance using domain-specific metrics in lab and field conditions.

Autonomous vehicle technology companies|Medical imaging device manufacturers|Industrial automation and robotics suppliers|Augmented reality and gaming studios|Retail security and analytics providers|Research institutes exploring smart cities

Start by contributing to data annotation pipelines or research prototypes. Publish internal reports demonstrating metric improvements, then own individual components such as object tracking. Over time, lead multi-disciplinary squads combining hardware, firmware, and software. Participation in open datasets challenges and patent filings strengthens professional reputation.

Vision technology is central to robotics, smart cities, and digital healthcare, ensuring robust career longevity. Specialists can advance to Principal Vision Scientist, Head of Perception, or CTO roles in hardware-centric start-ups. Expertise in edge optimisation and multimodal fusion will remain highly prized.

OpenCV for classic image processing tasks|Convolutional neural networks for feature extraction|TensorRT and ONNX for model optimisation|CUDA programming for GPU acceleration|Edge deployment on ARM and NVIDIA Jetson|Synthetic data generation and augmentation|Benchmarking using mAP, IoU, F-score metrics

Attention to detail in data labelling|Cross-disciplinary collaboration with hardware teams|Experimental rigour and statistical analysis|Documentation for safety-critical approvals|Creative problem solving under resource limits|Time management across concurrent experiments