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

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.

Develop and enhance control algorithms for autonomous trucks, focusing on motion planning, real-time operation, and debugging robotic systems.

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.

The Senior Software Engineer will enhance mapping infrastructure, develop large-scale map systems, optimize performance, and collaborate with cross-functional teams.

Develop deep learning perception models and frameworks for autonomous driving. Oversee projects from ideation to deployment and collaborate across teams.

Design and develop Bird’s Eye View fusion models for autonomous driving using multimodal sensor inputs like LiDAR, focusing on performance, robustness, and scalability.

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