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Waymo is looking to improve its autonomous driving technology by enhancing the Perception team's system, which learns the spatial-temporal representation and semantic meanings of the surrounding environment of the self-driving car.

Requirements

• Experience with Python
• Experience with ML frameworks like PyTorch or JAX
• 7+ years experience in Machine Learning and/or Computer Vision
• Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
• MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
• Experience with C++
• Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI

Responsibilities

• Own the panoptic segmentation task (instance segmentation and semantic segmentation), take responsibility for task scaling and task performance, take ownership of aligning instance segmentation and object detection/tracking (in particular in an end-to-end architecture), create ML methods and recipes to scale and improve tasks
• Collaborate with ML engineering/research teams to develop efficient model architectures for representing occupancy and panoptic segmentation, and train and deploy such models with a focus on using large pre-trained models
• Collaborate with partner teams to establish efficient human and machine labeling workflows
• Analyze panoptic segmentation issues in real-world application, identify issues and root causes, advise or develop short- and long-term solutions.
• Develop and maintain metrics for 4D (3D + time) instance segmentation and semantic segmentation

Other

• Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
• 7+ years experience in Machine Learning and/or Computer Vision
• MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
• Travel requirements not specified
• Clearance requirements not specified