Driver Workload Estimation AI Engineer, Info Mobility Car
Core
Develop ML-based algorithms to estimate driver workload (busyness) using vehicle CAN signals, in-vehicle sensors, and driver operation logs to enable safer driving suggestions and voice prompts.
Role type
Senior IC machine-learning engineer (driver state estimation)
Builds
Driver support features providing driving suggestions and voice prompts
Domain
Automotive / Autonomous Driving / Driver Monitoring
Deliverable
production ML models
Required skills
Machine learning, deep learning, statistical modeling, time-series data analysis, sensor fusion, feature engineering, Python, PyTorch, TensorFlow
Preferred skills
Driver state estimation, vehicle dynamics, edge/embedded optimization, simulator evaluation, Unity
Technologies
Python, PyTorch, TensorFlow, CAN signals, in-vehicle sensors, simulators
Responsibilities
Design and implement ML-based driver workload estimation algorithms; Build and operate training data infrastructure and evaluation pipelines; Investigate and improve logics combining CAN-based and vision-based workload indicators; Design interfaces to feed workload results into driving suggestion logic; Collaborate with software, test, and UX engineers to align on requirements and metrics; Participate in simulator and on-road evaluations to drive improvement cycles
