About the job
As a TLM for Scene Understanding, you will act as a true "player-coach" for a team of roughly 6-10 engineers. This is a high impact role, where your models will directly dictate how the Waymo Driver reacts to complex, unstructured environments like active construction zones and temporary traffic signs. This work is critical to Waymo's ability to scale into new cities, across the US and internationally.
Responsibilities
Own a specific domain within scene understanding, such as traffic controls or construction zones, and work with product and safety partners on short- and long-term improvements in support of Waymo’s scaling goals
Lead the analysis of real-world scene understanding issues to develop technical roadmaps and drive the roadmap execution,
Build resilient and high performing teams through people development and hiring,
Make project staffing decisions, technical decisions, drive escalations; ultimately accountable for delivering projects.
Qualifications
Minimum
Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
7+ years of experience building and deploying deep learning/computer vision models in production environments, ideally within the AV or robotics space
2-3+ years of experience directly managing and scaling engineering/research teams (managing 5+ reports)
Fluency in Python, C++, and deep learning frameworks (PyTorch, JAX)
Preferred
MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
Publications at top-tier conferences like CVPR, ICCV, ECCV, NeurIPS,.
Experience with C++
Experience with real-time system design