Senior Onboard ML Integration Engineer

42dot; Sunnyvale (CA); On-site; USD 200,000 - 300,000; Full time

Job summary

42dot is seeking a seasoned engineer to bridge ML autonomy models with the on-board software on vehicle hardware. You will own end-to-end deployment, running models in real time with strict latency and safety constraints, and shaping the deployment tools that move artifacts from training to vehicle-ready binaries.

You will optimize inference, manage hardware resource usage, and collaborate with ML researchers to ensure deployments meet the rigorous demands of automotive software.

Qualifications

• Track record of grit and ownership in challenging deployments.
• 5+ years in systems or software engineering with ML inference or real-time software.
• Experience deploying ML models in production on resource-constrained hardware.
• Strong C++ and Python skills across ML and systems boundary.

Responsibilities

• Integrate ML 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 and resource contention.
• Define interface contracts between ML models and the on-board software stack.
• Collaborate with the ML autonomy team to align deployment constraints with model design.

Skills

Grit and ownership

Team collaboration

Education

Bachelor's / Master's / PhD in CS/EE/Robotics

Tools

C++

Python

TensorRT

ONNX Runtime

Embedded systems

RTOS

Job description

42dot is seeking a seasoned engineer to bridge ML autonomy models with the on-board software on vehicle hardware. You will own end-to-end deployment, running models in real time with strict latency and safety constraints, and shaping the deployment tools that move artifacts from training to vehicle-ready binaries.

You will optimize inference, manage hardware resource usage, and collaborate with ML researchers to ensure deployments meet the rigorous demands of automotive software.