Driver Workload Estimation AI Engineer

Woven by Toyota's Info Mobility Car team develops driver-support features that give driving suggestions and voice prompts, using in-cabin and external camera images and vehicle sensor data, with driver "busyness" estimation as the core technology. The Driver Workload Estimation AI Engineer leads development of machine-learning algorithms that estimate driver workload from vehicle CAN signals, in-vehicle sensors and driver operation logs as time-series data.

The engineer designs and refines robust workload indices and balances them with other indicators such as surrounding-vehicle and vision-based measures, builds and runs training-data infrastructure and evaluation pipelines (label and annotation policy, preprocessing, feature engineering), and designs interfaces and specifications that feed the estimates into the suggestion and voice-prompt logic. Work is done with software engineers, test engineers and UX members and calls for comfort in a high-uncertainty domain where hypotheses are tested iteratively with data.

Expertise in driver state estimation, vehicle dynamics, sensor fusion and machine learning is welcomed.