The Machine Learning Engineer for Search and Shopping at Google will focus on developing advanced machine learning architectures to enhance ad prediction models. This role involves collaborating closely with teams like DeepMind and Google Research to create low-latency solutions that maximize Tensor Processing Unit capabilities. The engineer will also work on integrating ads into AI-driven search experiences and improving auction dynamics. This position requires a blend of technical expertise and leadership in a fast-paced environment.

• Bachelor's degree or equivalent practical experience.
• 8 years of experience with software development, including 5 years of experience with large-scale machine learning, deep learning, neural networks, or recommendation systems.
• Experience designing and implementing large-scale production deep learning or neural network architectures under latency and computational constraints.
• Experience leading cross-functional technical projects and mentoring other engineers.

• Lead the technical architecture, delivery, and cross-team strategy for Search and Shopping Ads predicted click-through rate models.
• Design, prototype, and scale high-capacity predicted click-through rate architectures that maximize modern Tensor Processing Unit capabilities.
• Develop modeling solutions to capture deep user history and nuanced attention signals.
• Engineer mathematical loss functions and calibration methods to translate complex business objectives into auction improvements.
• Build agentic machine learning workflows to automate and accelerate optimal model architecture and feature space discovery.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.