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As a Senior Data Engineer on the Waymo Commercialization team, you will design data models, build data warehouse solutions, analyze raw data for insights, and collaborate with cross-functional teams to align data solutions with business needs while ensuring data quality and compliance.

As a Staff Data Engineer at Waymo, you will design and build data infrastructure, create and implement data models, and develop data warehouse solutions to support ride-share fleet optimization. You will collaborate with various teams within the organization to understand data needs and ensure the integrity and quality of data for commercialization efforts.

As a Senior iOS Engineer at Waymo, you'll develop an iOS app to control autonomous vehicles, focusing on user experience and communication between devices. You'll collaborate with various teams to ensure a seamless user interface and trust in the technology.

Waymo is seeking research engineers to work on building ultra-realistic autonomous vehicle simulations using machine learning techniques. The role involves collaborating with teams to improve simulation realism, designing experiments, developing metrics, training large models, and integrating them into the simulator. Preferred qualifications include a strong background in deep learning, coding skills, experience in ML techniques, and expertise in data analysis. Experience in autonomous vehicles is a plus.

Design, implement and test system software components, Linux Kernel device drivers, and other components for high-performance embedded systems at Waymo. Take on complex problems and provide clean solutions. Work closely with engineering teams.

Maximize performance of neural networks by enhancing and extending production grade compiler. Develop deep understanding of unique neural network inference platform and state-of-the-art neural networks. Implement compiler support for novel features of high-performance architecture.

Analyzing and optimizing code performance, designing and implementing compiler support, collaborating with hardware architects, and tuning neural networks for better efficiency and accuracy.