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The role involves developing visualization frameworks for autonomous driving technology, collaborating with teams to enhance development workflows and produce high-quality visualizations.

Design and develop robust data processing systems and pipelines, implement data storage solutions, and ensure system integrity through testing and monitoring.

As a Software Engineer in ML Infrastructure, you will build automated resource provisioning, optimize workload scheduling, manage large-scale data processing, and enhance feature management for model development.

Design and develop scalable frameworks for large-scale workloads in cloud and on-premise clusters, optimizing their efficiency and collaborating with application teams.

Develop large-scale data processing systems for autonomous driving, including storage, dashboards, and data pipelines, while ensuring integrity and resilience.

Develop high-quality visualization platforms for autonomous technology, work with autonomy engineers, and create polished visualizations for external applications.

Design and develop scalable computing infrastructure, optimize workloads, and collaborate with teams to enhance business-critical applications at Nuro.

Design and develop data pipelines for autonomous driving systems, create storage for data metrics, build dashboards, and maintain data integrity, focusing on ML components.

Develop and maintain scalable and reliable data annotation systems, implement data quality metrics, and apply ML research to optimize the data lifecycle.

Responsible for designing and developing scalable data pipelines, storage systems, and monitoring tools for ML data infrastructure, ensuring system integrity and performance evaluation.