Waymo is looking to develop state-of-the-art ML models for scene understanding around construction, emergency scenes, mapless driving and world changes to improve the safety, compliance, and scalability of Waymo's autonomous driving service.
Requirements
- 4+ years of experience in Machine Learning, with a strong focus on computer vision and/or deep learning for perception tasks.
- Deep understanding of state-of-the-art ML techniques for object classification, detection, tracking, pose estimation, and/or action recognition.
- Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
- Experience with multi-modal perception systems (e.g., combining camera, lidar, radar data).
- Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
- Experience in optimizing ML models for on-device deployment and real-time performance.
- Background in autonomous driving, robotics, or a related safety-critical domain.
Responsibilities
- Develop state-of-the-art ML models to understand complex scenes, including construction zones, emergency situations, mapless driving, and world changes.
- Work on the end-to-end ML pipeline, from data mining and labeling to training and deployment of models.
Other
- Hybrid role
- Publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
