About

• Design and prototype unified token-based architectures that treat text and image data as sequences for coherent multimodal generation Build scalable training pipelines for large-scale image-text datasets using discrete tokenisation (e.g. VQ-VAE, DALL*E-style encoders). * Experience deploying models to production or on-device environments. Experience optimizing models for Neural Processing Units (NPUs) or other hardware accelerators. Knowledge of quantization, pruning, and efficient fine-tuning techniques. Experience with prompt engineering, instruction tuning, and RLHF. Exposure to video generation and temporal modeling. Experience mentoring junior scientists or engineers. Strong collaborative skills across cross-functional teams.