Sr. Software Integration Engineer, Autonomy

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.

• Integrate ML models (end-to-end driving, VLA, world models) onto the on-board compute and runtime stack
• Optimize model inference for latency, throughput, memory, and power on embedded automotive hardware
• Build and maintain the model deployment pipeline, including conversion, validation, and rollout
• Stabilize on-vehicle ML execution by diagnosing runtime failures, timing violations, and resource contention
• Define interface contracts between ML models and the rest of the on-board software stack