Develop end-to-end machine-learning models for autonomous-driving taxis from camera and LiDAR data, then evaluate and optimize them in simulation and real vehicles.
About this role
The Technical Program Manager drives the overall autonomous-driving development program toward the planned 2028 commercialization of Level 4 taxi services.
Responsibilities include designing quarterly plans, long-term roadmaps, milestones, and review structures. The role coordinates across ML, vehicle, embedded, data and infrastructure, simulation and evaluation, and safety and operations teams. It connects models, algorithms, research results, and platform technologies to product and vehicle implementation, moving work from proof of concept through real-vehicle validation, limited operation, and commercialization preparation. The TPM organizes technical issues, supports implementation prioritization and Go/No-Go decisions, and documents specifications, dependencies, risks, and decisions so that multiple teams can work from shared assumptions.
The role plans data collection, real-vehicle evaluations, validation operations, incident response, and operational preparation. Findings from field work, transportation operations, and experiments are fed back into development plans. External coordination includes requirements alignment with municipalities, transportation operators, OEMs, suppliers, research institutions, and other external partners. The role also supports consensus building, schedule coordination, and issue management needed for demonstrations and deployment.
Safety, quality, and operational-readiness responsibilities include making risks visible from the perspectives of safety, reliability, operability, and observability. The TPM establishes and continuously improves review, record-keeping, reporting, and validation processes. Progress, issues, and decisions are shared clearly, while specifications, discussion points, and dependencies are organized for cross-functional transparency.
The development context includes Physical AI, VLA, and end-to-end autonomous-driving models intended to operate in the real world alongside vehicles, roads, people, and traffic rules. Newmo has its own taxi and hire-car business and fleet, providing driving data, sensor data, and field knowledge that can be fed directly into development. The stated development process uses an internal platform to apply fleet data to learning, validation, and improvement, extending beyond desk-based PoCs toward autonomous-driving systems that function in real-world conditions. The program involves internal ML, software, vehicle, operations, and policy-relations teams. The posting also states participation in the METI/NEDO GENIAC program, a national project in Sakai City related to autonomous-driving implementation, and collaboration with companies leading autonomous-driving software.
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