Develop and optimize machine learning models for autonomous vehicle motion prediction and planning, collaborate across teams for integration, and deploy models on edge devices while ensuring performance.

Develop and optimize ML models for vehicle behavior and motion planning, contribute to data processing, deploy models on embedded systems, and collaborate across teams.

Develop and optimize behavioral AI models, implement architectures for agent prediction, deploy machine learning models on edge devices, and collaborate with multidisciplinary teams in autonomous vehicle technology.

The ML Engineer will develop and optimize deep learning models for BEV space, analyze data, and ensure system reliability through cross-functional collaboration.

Develop and optimize multimodal perception models using deep learning techniques for autonomous driving. Responsibilities include model training, data analysis, and architectural design, collaborating with various engineering teams to ensure system reliability.

The role involves developing and optimizing multi-modal perception models, collaborating with cross-functional teams, and ensuring real-time performance of machine learning systems in autonomous vehicles.

Develop and optimize ML models for autonomous vehicles, focusing on computer vision, deep learning, data management, and cross-functional collaboration.

The Machine Learning Engineer II will optimize ML model execution on GPU platforms, develop App Engine SDK features, and ensure code quality.

Develop and maintain components for an ML runtime and SDK on embedded GPUs, assist in data handling between compute nodes, and contribute to testing and performance tuning.

Lead the newly established App Engine team focused on integrating deep learning models into an autonomous trucking platform. Ensure reliability and scalability through effective management, technical direction, and collaboration with cross-functional teams.

The HR Business Partner collaborates with management to drive HR initiatives, enhance team performance, and manage talent development while advising on employee relations and legal compliance.

The Software Engineer II will develop and maintain ML training infrastructure, support distributed model training, collaborate with teams, and enhance ML operations.