Senior Machine Learning Engineer, Perception, Scene Understanding

The Perception Scene Semantics team is responsible for developing the state-of-the-art ML models for scene understanding around construction, emergency scenes, mapless driving and world changes. The team works on the end to end ML pipeline from data mining, labeling, training onboard / offboard models, and deployment. The team supports multiple top company priority areas that ensures safety, compliance, and scalability of Waymo's service.

In this hybrid role, you will report to the Technical Lead Manager of Scene Semantics.

You will:

• 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.

You have:

• 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).

We prefer:

• PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
• 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.
• Publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).

#LI-Hybrid