Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…

Summary: Meta runs one of the largest server fleets on earth, and every product bet (AI training, ranking, inference, storage) turns into a demand for compute that we must forecast, shape, and match to a physical supply of servers, racks, power, and data center space. As the senior technical owner of Server Demand Planning, you own the demand side of that equation and close the loop with supply: you forecast long- and near-term server capacity demand by rack/hardware type and region, and you bu…