Driver Workload Estimation AI Engineer, Info Mobility

Woven Planet

Driver Workload Estimation AI Engineer at Woven by Toyota developing algorithms for driver workload estimation. Focused on leveraging machine learning and vehicle sensor data to innovate in mobility.

Posted 5/29/2026full-timeTokyo • 🇯🇵 JapanMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, implement, and enhance ML-based driver workload (busyness) estimation algorithms that take vehicle CAN signals, various in-vehicle sensors, and driver operation logs as time-series inputs
Build and operate training data infrastructure and evaluation pipelines, including label and annotation policy design, data preprocessing, and feature engineering
Investigate and improve logics that combine CAN-based workload indicators with other workload measures, such as surrounding-vehicle information and image/vision-based indicators
Design interfaces and specifications to feed workload estimation results into driving suggestion and voice prompt logic, and continuously improve overall feature performance
Collaborate with software engineers, test engineers, UX members, and other stakeholders to align on requirements and evaluation metrics, and to organize and share experiment results and technical learnings
Participate, as required by projects and business needs, in planning and conducting evaluations using simulators and on-road test vehicles (including business trips), and drive improvement cycles based on real-world findings

Requirements

What you’ll need

3+ years of practical experience in software or algorithm development primarily using vehicle CAN signals, in-vehicle sensors, and driver operation logs as time-series data
Practical experience developing algorithms using machine learning, deep learning, and/or statistical modeling
Development experience in Python using major ML/DL frameworks (e.g., PyTorch, TensorFlow)
Ability to independently drive the end-to-end ML development process from data preprocessing and feature design through training and evaluation
Communication skills to work with multiple stakeholders and clearly explain technical topics and evaluation results
Willingness to travel for business purposes as required by project or business needs
Business level Japanese proficiency and conversational level English

Benefits

Comp & perks

Competitive Salary - Based on experience
Work Hours - Flexible working time
Paid Holiday - 20 days per year (prorated)
Sick Leave - 6 days per year (prorated)
Holiday - Sat & Sun, Japanese National Holidays, and other days defined by our company
Japanese Social Insurance - Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance
Housing Allowance
Retirement Benefits
Rental Cars Support
In-house Training Program (software study/language study)

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Hard Skills & Tools

machine learningdeep learningstatistical modelingalgorithm developmentdata preprocessingfeature engineeringtime-series dataPythonPyTorchTensorFlow

Soft Skills

communication skillscollaborationindependent workproblem-solvingstakeholder engagement