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# Principal Engineer, Resource Optimization and Fleet Logic

- **Company:** Google LLC
- **Location:** Thornton, CO, United States
- **Salary:** $307,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Centers, Distributed Systems, Network Topologies, Infrastructure as a Service (IaaS), Graphics Processing Unit (GPU), Heroku, Information Technology, Machine Learning Operations
- **Published:** September 17, 2026
- **Apply:** https://dejobs.org/x/x/4CD5E00A6071431FADC39748CB55CFE3/job/

## About the Role

* Bachelor's degree in Computer Science or similar technical field, or equivalent practical experience.
 * 15 years of experience as a software engineer.
 * Experience delivering large-scale capacity planning, IaaS/PaaS solutions, or fleet management systems., * Master's degree or PhD in Computer Science or a field related (e.g., Networking or Security Systems).
 * Experience architecting, leading, and delivering large-scale capacity planning, combinatorial optimization, fleet management, or distributed infrastructure transformations from concept to deployment.
 * Deep understanding of modern AI/ML infrastructure demands (TPU/GPU topologies, accelerators) with the ability to integrate AI-driven solutions.
 * Ability to influence and lead without direct authority, building strong cross-organizational relationships across disparate teams (e.g., Hardware, Software, Supply Chain, and Product Management).
 * Exceptional communication skills, and ability to articulate complex mathematical, economic, and architectural concepts to engineering leaders and executive business stakeholders.

## Description

* Lead the design and evolution of next generation global fleet planning, defining a multi-year engineering roadmap to deliver 10x more data center capacity with ML, compute & storage resources.
 * Leverage deep technical knowledge across the data center stack, spanning ML hardware (TPUs/GPUs), general compute, power, cooling, physical space, supply chain workflows, and network topology to model, forecast, and dynamically reconfigure fleet resources.
 * Partner across AI & Infrastructure organizations to define a unified capacity management product suite meeting AI training and inference for internal and external customers.
 * Integrate cutting-edge AI/ML, operations research, and advanced mathematical optimization into capacity planning workflows to compress capacity cycles, eliminate stranded capacity, and maximize data center utilization.
 * Collaborate with academic institutions and industry pioneers to anticipate technology trends.


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