Research Engineer

• Model Development: Research, design, and implement state-of-the-art computer vision models (e.g. Vision Transformers, SAM, MambaVision, Segment Anything, Diffusion Models).
• Algorithmic Optimisation: Translate the latest deep learning research into performant, production-ready systems.
• Scalable Vision Systems: Build distributed training and inference pipelines optimised for large-scale datasets (e.g. WSI, medical, industrial, or satellite imagery).
• Multi-Modal Learning: Integrate vision with other modalities (e.g. text, genomics, spatial omics, or language) to build cross-domain AI systems.
• Performance Engineering: Profile training workloads, optimise GPU utilisation, and accelerate inference through efficient data pipelines, caching, and mixed-precision training.
• Collaboration & Mentorship: Partner with ML researchers, engineers, and domain experts to deliver high-impact solutions and guide junior engineers.
• Project Leadership & Client Engagement: Lead and manage end-to-end machine learning projects, coordinate cross-functional teams, and act as the primary technical point of contact with clients to ensure successful delivery and alignment with project goals.

Senior Research Engineer – Computer Vision

Research Engineer