Overview
We 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.
Responsibilities
- Train, 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.
Requirements
- Degree 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.
