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This role involves developing and optimizing machine learning models for autonomy, managing datasets, enhancing training pipelines, and collaborating across teams to integrate ML solutions in autonomous vehicles and delivery robots.

Develop and implement on-board localization and cloud mapping algorithms, optimizing rover localization accuracy and cloud mapping processes in challenging environments.

The ML Platform Engineer will build scalable architecture for ML training workloads, optimize system performance, and collaborate with teams for enhanced efficiency on Kubernetes.

As a C++ Software Engineer, you will develop and optimize control systems for autonomous vehicles, focusing on trajectory tracking and real-time performance using modern C++ and advanced algorithms.

The role involves developing and maintaining embedded Linux systems for autonomous vehicles, including device drivers and low-level userspace software.

As a Machine Learning Engineer Intern, you will work on advanced projects involving 3D perception, data engineering, and audio signal processing for autonomous vehicles, alongside a mentor.

The Research Engineer Intern will work on ML models for autonomous vehicles, designing algorithms, running experiments, and improving simulation behavior.

Design and maintain scalable CI/CD infrastructure for multi-platform software, optimize build performance, manage dependencies, and support development teams.

The Lead Software Engineer will design and evolve API and UX for the Pipeline, enhance developer productivity, manage project timelines, and streamline development across teams.

The Embedded Tools Engineer will design and maintain CI/CD pipelines, develop testing tools for embedded systems, and ensure software quality for autonomous vehicles and robots.