Field Optimization

About The Role AIM builds autonomous machines that must continuously improve as they operate in the real world. Performance is not theoretical - it’s measured in productivity, efficiency, and predictability on real jobsites. Field Optimization Engineers focus on making autonomy better at real tasks, closing the loop between field behavior and AI, planning, and control systems. About you You are analytical, curious, and deeply interested in how autonomous systems behave under real conditions. You enjoy working with operators, data, and models to improve performance over time. You are equally comfortable: analyzing autonomy performance metrics and error distributions observing operators and understanding task-level workflows diagnosing why a behavior works in theory but fails in practice translating field observations into model and planning improvements validating changes through real-world testing You believe the field is the ultimate teacher - and that learning from it is a competitive advantage. About us together Together, we will: improve task performance across dozing, excavation, loading, and more identify the signals that make autonomy more robust and adaptive validate learning and model improvements in the real world feed high-quality insights back into AI and planning teams turn field variability into system strength We’ll iterate relentlessly, test under stress, and make autonomy measurably better with every deployment. Responsibilities Task Optimization & Perfor