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The Principal Engineer will design and implement real-time algorithms for sensor fusion and localization, ensuring precision in autonomous vehicle navigation, and will mentor other engineers.

The role entails integrating and optimizing on-vehicle AD systems, collaborating on diagnostics and vehicle platform integration, while conducting on-site testing.

Develop and deploy machine learning algorithms for planning in autonomous trucks, ensuring safety and real-time efficiency.

As a Senior ML Infrastructure Engineer, you will design scalable architectures for ML, build robust data pipelines, manage GPU clusters, and drive improvements in CI/CD workflows while collaborating with cross-functional teams.

Develop and optimize core infrastructure for autonomous driving. Focus on low-latency execution, component health monitoring, and system performance improvements.

The role involves developing ML-based planning algorithms for autonomous trucks, ensuring safety checks, real-time operation, and keeping up with research. Requires strong communication and collaboration.

Develop motion planning software for autonomous trucks, utilizing sensor data to enhance planning algorithms and collaborate with engineers.

Lead the integration of components into vehicles, manage issues, conduct preventive maintenance, and collaborate with engineers. Must troubleshoot and document activities.

Design and develop mechanical systems for autonomous trucks, ensuring integration with OEM vehicles and collaboration with cross-functional teams.

Develop and apply deep learning and data analysis techniques to create scalable vehicle simulation models, collaborating with teams to advance autonomous technology.