Staff Tech Lead, Machine Learning Engineer, Perception
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El puesto
Own and scale the panoptic segmentation task, covering instance and semantic segmentation, and align it with object detection and tracking in an end-to-end architecture.
Develop efficient model architectures for representing occupancy and 4D (3D + time) segmentation, prioritizing training with large pre-trained models and scalable deployment.
Collaborate with ML engineering and research teams to craft reliable recipes and methods that improve accuracy and efficiency at scale.
Partner with teams to establish robust labeling workflows for humans and machines, ensuring high-quality data for model training.
Analyze real-world segmentation issues, identify root causes, and propose practical short- and long-term solutions.
Create and maintain metrics for 4D instance and semantic segmentation, driving ongoing performance improvements and system integration.
Develop efficient model architectures for representing occupancy and 4D (3D + time) segmentation, prioritizing training with large pre-trained models and scalable deployment.
Collaborate with ML engineering and research teams to craft reliable recipes and methods that improve accuracy and efficiency at scale.
Partner with teams to establish robust labeling workflows for humans and machines, ensuring high-quality data for model training.
Analyze real-world segmentation issues, identify root causes, and propose practical short- and long-term solutions.
Create and maintain metrics for 4D instance and semantic segmentation, driving ongoing performance improvements and system integration.
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