Research Engineer - Generative modelling

Your background should include experience in ML and expertise in implementing seq2seq models. Ideally, you will be skilled in computer vision topics such as lip-sync, talking heads, audio-visual integration, face generation, and face rendering. Familiarity with key architectures such as Transformers, Diffusion models, GANs, and VAEs is essential, along with knowledge of cutting-edge research aimed at real-time and state-of-the-art generative vision.