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- Autonomous Driving Fusion Algorithm Engineer (MOT / Multi-Sensor Fusion)
JOB ID 28258
Autonomous Driving Fusion Algorithm Engineer (MOT / Multi-Sensor Fusion)
- Manufacturer, Manufacturer-Automotive
- IT, Product Engineer (Hard/soft)
- Tokyo
- ¥10,000,000~¥20,000,000
A Japanese deep tech startup founded in April 2024. Specializing in the development of autonomous driving systems for large trucks, it aims to solve challenges faced by Japan's logistics industry, such as driver shortages, aging populations, and increasing logistics demand. Focusing on trunk line transportation using expressways, it promotes improved transport safety, operational efficiency, and reduced logistics costs through advanced AI-powered autonomous driving technologies. Through collaboration with automakers and logistics companies, it is working on the practical use of autonomous trucks and the construction of next-generation logistics infrastructure.
A Japanese deep-tech startup established in April 2024, specializing in the development of autonomous driving systems for heavy-duty trucks. The company aims to transform Japan’s logistics industry by addressing challenges such as driver shortages, an aging workforce, and increasing freight transportation demand. Focusing on autonomous highway transportation, it develops advanced AI-powered technologies designed to improve transportation safety, operational efficiency, and logistics sustainability. Through collaboration with automotive manufacturers and logistics companies, the company is working toward the commercialization of autonomous trucking solutions and the development of next-generation automated freight transportation infrastructure in Japan.
This role focuses on multi-object tracking (MOT) and multi-sensor fusion for autonomous driving perception, covering both object-level fusion and early fusion. The position is responsible for advancing data association and state estimation algorithms, cross-sensor fusion architecture, evaluation methodology, and the deployment of robust, production-grade tracking and fusion modules on large-scale real-world driving data
Job Description
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- Responsibilities
- - Design and iterate on multi-object tracking (MOT) algorithms for autonomous driving, including data association, state estimation (KF/EKF/UKF/IMM, etc.), track lifecycle management, and handling of occlusions and ID switches, to improve tracking stability in complex urban and highway scenarios.
- Develop object-level fusion algorithms that perform spatio-temporal alignment, cross-sensor association, and confidence fusion of detection results from Camera / LiDAR / Radar, producing a unified and stable object list.
- Participate in the design and deployment of early fusion solutions, including spatio-temporal synchronization of multi-modal data and alignment/fusion strategies for raw or feature-level data.
- Analyze fusion and tracking bad cases from real-world road tests and simulation data, build evaluation metrics and automated benchmarking pipelines, and continuously improve algorithm performance.
- Own the engineering, performance optimization, and mass-production delivery of algorithms on embedded automotive platforms.
- Collaborate closely with perception, localization, calibration, planning & control, and data platform teams to define interface specifications for the fusion module.
-
- Requirements
- Requirements
- Master's degree or above in Computer Science, Automation, Electronic Engineering, Control, Robotics, or a related field.
- 2+ years of R&D experience in perception/fusion algorithms for autonomous driving or robotics, with a solid foundation in probability theory, state estimation, and optimization.
- Deep understanding of multi-object tracking and multi-sensor fusion methods; familiar with the Kalman filter family, IMM, and data association algorithms such as JPDA, MHT, and the Hungarian algorithm.
- Familiar with the characteristics and error models of Camera, LiDAR, and Radar sensors; experienced in spatio-temporal synchronization and extrinsic calibration.
- Proficient in C++ and familiar with Python, with strong coding standards and engineering skills; experienced with common libraries such as Eigen, PCL, and OpenCV.
- Familiar with ROS/ROS2 or autonomous driving middleware (e.g., Apollo, Autoware, CyberRT) development workflows.
- Strong analytical and problem-solving skills, good communication and teamwork, and a strong sense of ownership.
-
- Preferred
- Preferred Qualifications
- Hands-on MOT project experience (e.g., SORT, AB3DMOT), or ownership of the tracking module in a mass-production program.
- Mass-production delivery experience with Camera + LiDAR + Radar object-level fusion.
- Research or deployment experience in early fusion.
- SLAM project experience (e.g., LIO-SAM, FAST-LIO, VINS) and familiarity with tightly coupled state estimation.
- Publications at robotics/autonomous-driving conferences such as ICRA or IROS, or strong results on public tracking/detection benchmarks such as nuScenes, Waymo, or KITTI.
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- Location
- Tokyo
-
- Work Style
- Remote working possible, Flex working possible
-
- Salary
- ¥10,000,000~¥20,000,000
-
- Attractive
Points - Japanese company with global opportunities, Weekends and holidays off, Major corporation
- Attractive
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