ドライバー運転負荷推定AIエンジニア・Info Mobility Car
Core
Develop ML algorithms to estimate driver workload (busyness) using vehicle CAN signals, sensor data, and operation logs to enable driver support features like suggestions and voice prompts.
Role type
Senior IC machine-learning engineer (driver workload estimation)
Builds
Driver support functions for Info Mobility Car
Domain
Automotive / Autonomous Driving / Driver Monitoring
Deliverable
production ML models
Required skills
time-series data processing, machine learning, deep learning, statistical modeling, Python, PyTorch, TensorFlow, feature engineering, algorithm design, data pipeline construction, stakeholder collaboration
Preferred skills
ADAS development, driver monitoring systems, robotics, vehicle sensor fusion, ML model production deployment (edge/embedded), simulator evaluation (Unity), external ML publications
Technologies
Python, PyTorch, TensorFlow, Unity, CAN bus
Responsibilities
Design and implement ML algorithms for driver workload estimation using vehicle data; Build and maintain learning data infrastructure and evaluation pipelines; Integrate workload metrics with other busyness indicators; Define interfaces for driver support logic; Collaborate with software, test, and UX teams; Participate in simulator and real-vehicle testing
Seniority
Senior, hands-on IC
