Staff TLM, Perception, Semantics Foundation

Waymo
Mountain View, California, USA / Mountain View (US-MTV-EMF680), Mountain View, California, United States2026-02-20

About the job

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 engineers like you to (1) develop methods for efficiently and continuously learn from large scale real-world data, (2) develop models and model training at scale, (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.

Responsibilities

Own an onboard perception model and platform that is critical for semantic understanding

Define the roadmap for the above and plan and execute long term improvements to support Waymo’s scaling goals

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

5+ years experience in Machine Learning and/or Computer Vision

2+ years in managing ML engineering or research teams

Experience with Python

Experience with ML frameworks like PyTorch or 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, ICLR, ICML, ICRA, RSS, NeurIPS, AAAI, IJCV, PAMI

Experience with C++

Experience with real-time system design