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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Raleigh, NC, USA; Durham, NC, USA.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in C or Python.
• 5 years of experience testing, and launching software products.
• 5 years of experience with performance, large scale systems data analysis, visualization tools, or debugging.
• 3 years of experience with software design and architecture.
• Experience with end-to-end performance analysis for deployed platforms to understand and mitigate performance bottlenecks.

Preferred qualifications:

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

About the job

In this role, you will be drive innovation through GenAI methods, revolutionizing performance optimization and efficiency across existing fleet infrastructure as well as next-generation platforms. You will apply AI/ML or other investigative techniques to improve performance/efficiency of key applications or the entire fleet. You will be responsible for identifying or prototyping new projects, taking them to production. In other words, you will make the goal of a "self-driving" autonomous fleet a reality.

You will be working with a small team of computer architects, compiler and efficiency experts, runtime system experts, and AI researchers. You will be collaborating with developers up and down the stack, including hardware, kernel, networking, and cluster management teams to implement and deploy your changes.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) 20% bonus target equity benefits

Learn more about benefits at Google .

Responsibilities

• Develop end-to-end performance analysis for deployed platforms to understand and mitigate performance bottlenecks.
• Identify opportunities and prototype AI/ML-driven approaches to improve on existing heuristics.
• Develop engineering driven methodology to inform the system architecture and design of all systems deployed in Google data centers.
• Work with the infrastructure and application teams to deploy novel solutions across Google's data-center fleet. This could include interacting with vendors to bring Google requirements into their roadmaps; and ensure the roadmap requirements are well understood and that the capabilities of the underlying platform are fully exploited.
• Design, develop, test, deploy, maintain and improve software systems.