Guide the technical blueprint for Fleet Transformation, ensuring Google's infrastructure manages Artificial Intelligence/Machine Learning (AI/ML) compute needs.
Design and architect simulation engines and solvers for multi-dimensional constraints (e.g., power, space, network) on global datasets with multiple variables.
Advance MIP models by migrating fleet optimizations from localized to integrated, cluster-wide solutions for better resource utilization and efficiency.
Guide the self-driving Fleet initiative by creating automated policy-enforcement layers and lifecycle actions.
Mentor engineers, promote cross-functional synergy with Planning and Data Center Operations, and ensure reliability of global systems.
Minimum qualifications:
Bachelor's degree in Computer Science, a technical field, or equivalent practical experience.
8 years of experience in designing and developing large-scale distributed systems and software.
Experience with large-scale distributed systems, software architecture, computational issues and advanced algorithms.
Preferred qualifications:
Experience with mixed integer programming/linear programming or data center capacity planning/management.
Experience with optimization problems or supply chain systems.
