Integrates ML models (end-to-end driving, VLA, world models) onto on-board compute and runtime, and optimizes inference for latency, memory, and power on embedded automotive hardware. Owns the model deployment pipeline (conversion, validation, rollout) and the interface contracts between ML models and on-board software. Stack is C++ and Python, with TensorRT and ONNX Runtime preferred.
We are looking for the best
42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles.
We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.
Great models are only as good as the system they run on. This role sits at the boundary between the ML autonomy team's models and the on-board system, taking what the research and ML teams build and turning it into something that runs reliably, in real time, on real vehicle hardware. 42dot is looking for builders who want to own the last and hardest mile between a model that works in an offline eval and a model that works in a vehicle.
The on-board integration architecture is being defined right now, with no legacy deployment stack to retrofit. An early hire here will help shape:
Responsibilities
Qualifications
Preferred Qualifications
Interview Process
Compensation
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