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As a GPU Software Engineer at Waymo, you will collaborate with application teams to optimize algorithms for GPU utilization. This includes building high-performance abstractions, improving compiler optimizations, and analyzing GPU performance. You will also co-design future hardware features.

The Charging Infrastructure Program Manager will provide strategic direction for the procurement, design, construction, and maintenance of EV chargers. Responsibilities include managing vendor teams, ensuring compliance with standards, enhancing service ticket resolution, and partnering with sustainability teams to meet carbon-free goals. The role demands strong communication and analytical skills to support decision-making.

The Technical Program Manager will lead cross-functional teams to drive the execution of projects related to the Waymo Driver. Responsibilities include risk management, setting up organizational efficiencies, and ensuring effective communication across the organization to meet product goals.

As a Systems Engineer at Waymo, you will collaborate with software engineers and product managers to develop system requirements, architectures, and verification strategies for depot automation features. Your role involves debugging issues, validating performance, and implementing improvements, while maintaining a strong focus on teamwork and results.

As a Software Engineer in the Sensors team at Waymo, you will engage in multidisciplinary collaboration focused on radar, cameras, and sensor architecture design. Responsibilities include maintaining cloud-based manufacturing and test infrastructure, embedded control for radar, and conducting software testing to ensure reliability of systems used in autonomous vehicles.

As a Software Engineer specializing in Computer Vision and Deep Learning at Waymo, you will develop multi-modal sensor fusion architectures and large-scale foundation models. You will also create data pipelines to enhance the Waymo Driver's capabilities using machine learning.

The Software Engineer will develop and deploy deep learning models, including vision language models (VLMs) and large language models (LLMs). Responsibilities include creating data mining and training pipelines and collaborating with research teams across Alphabet, leveraging vast driving data for model development.