anomaly detection, predictive maintenance, demand forecasting, network optimisation, signal processing Research novel approaches when existing methods fall short, read papers, run experiments, iterate Implement algorithms from scratch when needed; understand what's happening under the hood Take models from research prototype through to production deployment Work with large-scale time … Looking For: First-Principles Understanding Candidates must demonstrate substantive depth in ML fundamentals, including the ability to: Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour ...