Waymo is the self-driving technology company with a mission to make it safe and easy for people and things to move around. Building on software and sensor technology developed at Google, Waymo is now launching the world’s first fully self-driving transportation service that will take members of the public from A to B at the touch of a button.
The Machine Learning Infrastructure team at Waymo builds the industrial scale machine learning platform used by ML practitioners developing software for our self-driving car. We provide essential tools and frameworks to support the entire lifecycle of machine learning at Waymo, from data processing, large scale training and evaluation frameworks to efficient neural net inference runtimes for onboard execution and simulation. We work hand in hand with machine learning experts in all parts of the company including perception, behavior prediction, planning, mapping, hardware, and simulation.
Join the Training Infrastructure group within Machine Learning Infrastructure, and help us make training and evaluating ML models at Waymo easier, faster, and better! We develop and maintain a set of frameworks and tools on top of Tensorflow that address many of the pain points experienced by ML practitioners: training fast and at scale, discovering optimal hyper-parameters, automatically retraining nets on a schedule, computing reliable and noiseless metrics on validation sets, and validating newly trained nets when deployed into the full onboard software stack. We collaborate with teams at Google and DeepMind to leverage their research and infrastructure, as well as develop our own in-house techniques.
Bonus Qualifications in one of the following, depending on the project: