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Develop algorithms for autonomous driving and create software for safe and intuitive motion planning. Collaborate with perception and control components, and mentor team members.

The role involves developing ML algorithms for autonomous driving, including training models, evaluating performance, and improving behavioral models.

The engineer will train, evaluate, and deploy ML models for understanding driving environments, focusing on motion prediction and planning for autonomous vehicles.

Responsible for training and deploying ML models for scene understanding, behavior prediction, and planning in autonomous vehicles. Collaborate on designing and analyzing experiments, maintaining evaluation code, and improving model performance.

As a Principal Engineer on the Behaviors team, you will guide the technology direction, lead complex initiatives, and mentor engineers to enhance autonomous vehicle capabilities through ML solutions.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

The Engineer will enhance developer productivity by creating and maintaining tools for the software development lifecycle, collaborating with teams to improve workflows, and ensuring efficient development processes.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.