On-Board ML Integration Engineer – Autonomy

42dot; Sunnyvale (CA); On-site; USD 150,000 - 205,000; Full time

Job summary

42dot, a mobility AI company and Hyundai's Global Software Center, seeks an engineer to bridge ML models and vehicle hardware. You will own end-to-end deployment: from model training artifacts to vehicle-ready binaries, ensuring real-time performance on embedded compute.

This founding-team opportunity focuses on inference optimization, on-board interface contracts, and close collaboration with ML autonomy to ship reliable software for autonomous driving.

Qualifications

• Bachelor’s or Master’s in CS, EE, robotics or related field.
• 2–4 years in systems or software engineering with ML inference exposure.
• Experience deploying or optimizing ML models in production.
• Strong C++ and Python skills across ML and systems.

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 from training artifacts to vehicle-ready binaries.
• Stabilize on-vehicle ML execution by diagnosing runtime failures and resource contention.
• Define interface contracts between ML models and on-board software.
• Collaborate with ML autonomy team to align deployment with model design.

Skills

Grit & ownership

C++ & Python

ML inference

Embedded systems

Real-time software

Education

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

Tools

CI/CD pipelines

TensorRT

ONNX Runtime

Real-time OS

Job description

42dot, a mobility AI company and Hyundai's Global Software Center, seeks an engineer to bridge ML models and vehicle hardware. You will own end-to-end deployment: from model training artifacts to vehicle-ready binaries, ensuring real-time performance on embedded compute.

This founding-team opportunity focuses on inference optimization, on-board interface contracts, and close collaboration with ML autonomy to ship reliable software for autonomous driving.