Machine Learning Engineer - On-device Control and Optimization, Core OSApple • United States
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Machine Learning Engineer - On-device Control and Optimization, Core OS
Apple
- United States
- United States
Über
We are developing on-device control systems that manage thermal and energy tradeoffs on Apple devices. This means building models that capture device dynamics, designing cost functions that encode explicit priorities, and shipping control loops that adapt to real-world conditions.\nWe're looking for a Machine Learning Engineer who can work across the full stack: analyzing field data to understand device behavior, prototyping control and ML algorithms, and getting them running on-device. The problems are messy - noisy sensors, changing hardware, competing objectives - and the solutions need to be simple enough to ship on constrained hardware.
MS or PhD in controls, robotics, electrical engineering, computer science, or other quantitative field - or BS with relevant experience\nExperience with model predictive control, optimal control, or reinforcement learning (sequential decision-making)\nExperience working from raw logs or sensor data - comfortable building analysis from scratch\nStrong Python skills; demonstrated ability to take a project from data exploration through working prototype
Experience with thermal systems, battery management, or energy optimization\nFamiliarity with embedded or resource-constrained environments\nHands-on ML experience - training models, evaluating tradeoffs, iterating on approaches rather than applying off-the-shelf solutions\nComfort with ambiguity - able to scope and drive work without detailed specifications\nTrack record of shipping models or control systems into production, not just research
Sprachkenntnisse
- English
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