Staff Machine Learning Engineer, Multi-Modal Perception

The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), 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 learning from large scale real-world data, to (2) develop models and model training at scale, to (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.

In this hybrid role you will report to a Technical Lead Manager.

- Own tasks in the ML Driver, take responsibility for task scaling and task performance, create ML methods and recipes to scale and improve tasks.

- Analyze behavior of ML systems in real-world application, identify issues and root causes, advise or develop short- and long-term solutions.

- Monitor ML systems in production, develop methods for automatically detecting issues or regressions, develop AI-aided analysis and debugging tooling.

- Develop and maintain metrics for ADV relevant issues, including safety-critical and longtail issues.

- Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience

- 5+ years experience in Machine Learning and Computer Vision

- 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, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI