Principal Machine Learning Integration Engineer

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September 11

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Motional

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Transport • Artificial Intelligence • Automotive

Motional is a leading company in the development of autonomous vehicles, focusing on making driverless transportation a safe, reliable, and accessible reality. A joint venture between Hyundai Motor Group and Aptiv, Motional has been at the forefront of driverless technology for decades, creating SAE Level 4 autonomous vehicles for ride-hail and delivery services. The company emphasizes safety and innovation, leveraging advanced machine learning and automotive technology to build fully driverless vehicles that integrate smoothly into mobility networks, providing an enjoyable experience for daily transportation and deliveries.

1001 - 5000 employees

Founded 2020

🚗 Transport

🤖 Artificial Intelligence

📋 Description

• Deploy ML-based motion planning and control models onto vehicle platforms, ensuring performance under resource constraints • Optimize models for inference speed, latency, and memory footprint without sacrificing accuracy or safety • Collaborate with motion planning, controls, and perception teams to integrate ML components into the end-to-end autonomous driving stack • Build scalable deployment infrastructure including evaluation pipelines, model packaging, benchmarking, and automated validation • Validate model performance in both simulation and on-road testing, analyze results and drive iterative improvements • Maintain production-quality code in C++ and Python • Ensure models run reliably in production under strict performance and safety constraints

🎯 Requirements

• BS/MS/PhD in Robotics, Computer Science, Electrical Engineering, or a related field • 4+ years of professional experience deploying ML systems in real-world robotics, embedded, or autonomous platforms • Strong software engineering skills in C++ and Python, with knowledge of modern development practices (code reviews, testing, CI/CD) • Hands-on experience with ML frameworks (PyTorch, TensorFlow) and model optimization for deployment • Familiarity with GPU acceleration, or inference optimization (e.g., TensorRT, CUDA) • Strong problem-solving skills and ability to debug complex systems under production constraints • Experience with autonomous vehicle motion planning, control algorithms (MPC, LQR, PID), or reinforcement learning–based methods (preferred) • Publications in relevant ML or robotics conferences (ICRA, NeurIPS, CoRL, RSS) (preferred) • Experience with ROS, AUTOSAR, or other real-time robotics frameworks (preferred) • Knowledge of numerical optimization and its applications in trajectory generation (preferred) • Must be eligible to work in the U.S.; new hires are verified through E-Verify

🏖️ Benefits

• Medical • Dental • Vision • 401k with a company match • Health saving accounts • Life insurance • Pet insurance • Additional compensation may include a bonus • Additional compensation may include company equity • Remote U.S. work arrangement