About the role
Responsibilities:
- End-to-End Ownership: Define problem statements in collaboration with business stakeholders. Design data strategies (collection, annotation, validation). Develop and experiment with computer vision models (detection, segmentation, OCR, etc). Optimise models for performance, scalability, and efficiency. Lead deployment across cloud and/or edge environments. Monitor production models and drive continuous improvements. Ownership across the idea, model, deployment, and business impact.
- Computer Vision Focus Areas: Image classification, object detection (e. g., defect detection and quality checks), video analytics, OCR and document understanding edge AI / real-time processing.
Requirements:
- Strong expertise in deep learning (CNNs, Transformers).
- Experience with PyTorch and/or TensorFlow.
- Understanding of model optimisation (latency, memory, scalability).
- Experience with MLOps and deployment pipelines.
- Ability to handle large-scale, real-world datasets.
- Leadership and Collaboration: Drive projects independently, mentor junior team members, and make architecture and technical decisions; collaborate with product, engineering, and business teams. Expected to lead, not just execute.