Design and implement on-device control systems for thermal and energy management Build and fit thermal models from lab and field data Prototype MPC and related control algorithms end-to-end, from data analysis through on-device deployment Analyze large-scale field telemetry to characterize device behavior and validate models Define and tune cost functions that encode system-level tradeoffs Collaborate with firmware, hardware, and platform teams to integrate control systems into the OSMS or PhD in controls, robotics, electrical engineering, computer science, or related field - or BS with relevant experience Experience with model predictive control, optimal control, or reinforcement learning (sequential decision-making) Strong programming skills in Python; comfort with C/C++ for on-device work Experience working with real-world sensor data (noisy, incomplete, high-volume) Demonstrated ability to take a project from data exploration through working prototypeExperience with thermal systems, battery management, or energy optimization Familiarity with embedded or resource-constrained environments Background in system identification or online parameter estimation Comfort with ambiguity - able to scope and drive work without detailed specifications Track record of shipping models or control systems into production, not just research. Within this org, the team develops end-to-end solutions utilizing on-device machine learning and control, creating new techniques from data analysis and prototyping.