Machine Learning Engineer, Data/Systems

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 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.

You will:

• Create foundation scale data sets and training recipes, develop methods and recipes for human and machine labeling of foundation scale data sets.
• Create methods and recipes for continuous data intake, selection and incremental updates of large models, develop methods for data mining and recipes for automated data collection/model update flywheels.
• Develop methods and recipes for evaluating real-world performance of models, and detecting regressions in model updates.
• Develop and maintain ground-truth free performance metrics.

You have:

• Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
• 3+ years experience in Machine Learning and/or Computer Vision
• Experience with Python
• Experience with ML frameworks like PyTorch or JAX

We prefer:

• 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
• Experience with C++