Senior Machine Learning Engineer, Perception, Scene Understanding

Waymo • Mountain View, CA

167d • $204,000 - $259,000

About The Position

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 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.

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).

Nice To Haves

• 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).

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.

Benefits

• Discretionary annual bonus program
• Equity incentive plan
• Generous Company benefits program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees