Manage AI and IoT projects from presales and requirements definition through client negotiations and PoC delivery. Coordinate engineers, scope, quality, schedules, and proposals across multiple projects.
Idein is a Tokyo-based edge AI company whose Actcast platform processes camera and sensor data on devices such as Raspberry Pi. It gives businesses a central way to deploy, monitor and update AI applications and devices remotely, while local processing supports low-latency analysis and limits the data sent to the cloud.
Retailers, manufacturers, logistics operators and security providers use Actcast for tasks such as customer-flow analysis and operational monitoring. Actcast bills application vendors monthly, based on the number of devices with their applications installed; end-user application fees are agreed with each vendor. In July 2026, it transferred its Phonoscape customer-service analytics business to TIPLOG while continuing to develop Actcast as its core physical AI platform.
- Salary range
- ¥7M – ¥12M
- Median
- ¥7.5M – ¥10M
- Remote or hybrid
- 100%
- Most requested
- Machine learning 7
- Python 3
- Docker 2
- Linux 2
- Git 1
- Japanese posting, level unstated 9
- Common areas
- Product management 2
- Project management 2
Measured from the 9 listings Ranked has live for Idein. Japanese level, visa signal and skills are AI-graded from each posting and can be wrong — confirm against the employer's original posting before applying.
9
open positions at Idein
Leads machine-learning projects from technical goal-setting through development and validation, coordinating stakeholders and small teams on edge AI and mobility algorithms. Primarily remote.
Lead Actcast customer implementations from PoC to production, designing API integrations and operations, applying machine-learning solutions, and supporting adoption. Primarily remote in Tokyo.
Manage Actcast’s backlog, requirements, Scrum delivery, stakeholder alignment, releases and incident decisions for an edge AI/IoT platform, with customer reporting and risk coordination.
Develop algorithms for route generation in autonomous driving systems, focusing on low-speed areas like commercial parking lots.
Develop radar machine-learning solutions through signal-processing research, data preparation, model design, implementation, and evaluation with engineers in a remote-led hybrid workplace.
Lead the development of machine learning algorithms to solve domain-specific challenges, contributing from a leadership position in both internal and contracted projects.
Develop and maintain IoT platform and firmware, focusing on server-side and infrastructure design.
Develop machine learning algorithms to solve domain-specific challenges and create new value.