Seeking a Data Scientist to leverage data analysis and machine learning for autonomous driving challenges, utilizing large datasets, collaborating with cross-functional teams, and optimizing algorithms.

Develop and implement advanced machine learning models for autonomous driving, focusing on deep learning, perception, and real-time performance optimization.

Design and implement software modules for autonomous systems, optimize performance, and provide architectural guidance for other teams.

Design and optimize software systems for deploying large deep learning models in autonomous vehicles, focusing on performance and efficiency.

This role involves developing deep learning algorithms for autonomous driving, optimizing neural networks, and leveraging multimodal datasets for reinforcement learning and decision-making.

Design and implement deep learning algorithms for autonomous driving, optimizing neural networks for real-time performance, and integrating multimodal data.

Develop and optimize AI infrastructure, including DataLoader SDKs and Dataset Management Systems, for large-scale model training and inference.

Design and implement computer vision systems focusing on in-cabin scenarios, including detection of occupants and understanding human actions.

Lead development and deployment of AI models focused on optimizing efficiency and performance for autonomous driving systems using advanced techniques like quantization and parallel computing.

Lead the development and deployment of AI models for autonomous driving, optimizing model inference and ensuring efficient deployment across hardware platforms.

Develop algorithms for ego pose tracking and static environment tracking, work with cross-functional teams to execute on target platforms.

The Data Infrastructure Engineer will analyze large datasets for edge cases in autonomous driving, collaborating with Machine Learning Engineers to improve safety and comfort.

The role involves researching and implementing deep learning for robotics, developing motion controllers, and evaluating RL techniques for real-world applications.

Develop and optimize machine learning compilers for autonomous driving models on general purpose GPUs, enhancing performance and efficiency.

Design, train, and deploy large deep learning models utilizing data from a fleet of vehicles to enhance autonomous driving solutions.

The role involves developing a software stack for GPGPU architecture, focusing on CUDA compatibility, performance modeling, and cross-functional collaboration in AI frameworks. Requires extensive experience in GPU software design.

The Senior Staff AI Engineer will design and maintain AI tools to enhance software processes and integrate LLMs into systems, focusing on improving developer productivity and autonomous driving capabilities.

The Staff Computer Vision Engineer will design and implement advanced computer vision systems for in-cabin scenarios, focusing on occupant and object detection, human action analysis, and ambiance perception.

The Staff Machine Learning Engineer will research, design, and implement advanced deep learning algorithms for autonomous driving systems, ensuring robust, real-time performance and model optimization.

Develop and maintain machine learning models for robotics applications, collaborate across teams, and contribute to innovative solutions in AI and mobility.