Member of Technical Staff - Research Engineer, Omni

Omni is where Liquid's vision and audio work converges into a single multimodal model, and the next directions, multimodal MoE and token-efficient encoders, are open problems. This is an end-to-end model training role: you will run open research, data, pre- and post-training, evals, and the inference and deployment path for Omni, working directly with the Omni lead and the vision and audio teams, with our Chief Science Officer close to the research. The team is small and has just shipped a release, so there is no layer between you and the model, and the training infrastructure is being consolidated now rather than inherited.