Machine Learning Project Manager / Technical Lead

This role is part of Idein’s AI Development Department, which develops machine-learning technologies for company and client challenges. The position combines project management with technical leadership in contracted AI development, including work related to edge AI and next-generation mobility.

The project lead defines technical objectives with internal and external stakeholders, clarifies ambiguous domain requirements, selects feasible technical approaches, plans delivery within time constraints, and manages investigation, development, experiments, and validation through completion. The role also identifies technical issues, plans solutions, and establishes processes, organizational structures, and operating practices. Practical development of machine-learning algorithms for next-generation mobility is included.

The stated onboarding path depends on team-management experience. Candidates with experience managing teams of approximately five or more may join as section leaders with coaching support, taking responsibility for projects, personnel, and relationships with commissioning clients. Candidates with less experience may initially join as members, manage projects involving one or two engineers, and progress to section leadership within three months. After six months, the section leader is expected to manage both contracted and other projects with support or delegated management from senior staff.

The department has approximately 15 members, including secondees from partner organizations, organized into groups of three to five. Work includes model development using servers and, depending on the project, optimization for vehicle ECUs and deployment to Raspberry Pi or Jetson devices. The technology stack named in the posting includes Python, PyTorch, GitHub, Slack, Google Workspace, Notion, Docker, Linux, computing clusters, and Raspberry Pi.

The department works on client projects such as optimizing driver-monitoring functions, including facial landmark and gaze detection, for low-cost CPUs; the edge AI camera “ai cast” for retail, manufacturing, smart-city, and vehicle-monitoring applications; and the multimodal conversational system “Saya,” which combines rule-based response retrieval, speech recognition, speech synthesis, and automated behavior generation for lip synchronization.

The workplace is primarily remote, with office attendance or business travel when necessary. The posting describes a discretionary work-hours system. Support includes mentor one-to-one meetings, biweekly meetings with managers, biweekly knowledge-sharing seminars, weekly Friday social gatherings, and weekly company meetings.