Machine Learning Engineer (Computer Vision)

OverviewWe are looking for a ML Engineer (Computer Vision – Model Engineering) to build, train, and improve computer vision models for real-world systems. The role focuses on model engineering, experimentation, optimisation, and production-facing ML pipelines within an AI-driven environment.ResponsibilitiesTrain, fine-tune, and evaluate computer vision models for tasks such as object detection, segmentation, classification, and video understanding.Improve model accuracy, robustness, and inference performance through experimentation and optimisation.Analyse model failures, edge cases, and real-world performance issues.Work with large-scale datasets, preprocessing, augmentation, and validation.Prototype and evaluate new computer vision techniques and models.Support model deployment, monitoring, and production ML pipelines.Collaborate with engineers and researchers to translate experiments into production improvements.RequirementsDegree in Computer Science, AI, Machine Learning, or related field.1–2+ years of hands-on experience in deep learning and computer vision.Strong proficiency in Python.Hands-on experience with PyTorch and/or TensorFlow.Experience training and fine-tuning computer vision models.Familiarity with Linux environments and command-line usage.Ability to modify and optimise models beyond basic configuration changes.Strong debugging, experimentation, and analytical skills.Exposure to MLOps / tooling such as Git, Docker, MLflow, ONNX, TensorRT, OpenCV, or FFmpeg is advantageous.