Role shape: Own Kyber's data and modelling layer: infer the temporal dependencies of live operations, learn how coordinators allocate, and close the loop between real-time execution and forward scheduling. Environment: Python, Postgres, AWS, time-series and sequence models, learned cost functions, imitation and reinforcement learning, data pipelines, evaluation harnesses, technical hiring, on-site deployment, close work with the optimization role. Experience: Minimum three years applying machine learning in production. Practical reality: direct customer contact, time in live operations starting on the airport ramp, meaningful founding equity, coding credits, London-based, remote only by exception, UK work authorization preferred.