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Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop models for panoptic segmentation and occupancy in 3D and over time.
In this hybrid role you will report to a Sr Staff Technical Lead Manager.
You will:
- 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
You have:
- 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
- Experience with Python
- Experience with ML frameworks like PyTorch or JAX
We prefer:
- MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
- Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
- Experience with C++
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