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Job Details
Posted date: Apr 29, 2026
Location: Seattle, WA
Level: Director
Estimated salary: $313,500
Range: $262,000 - $365,000
Description
Manage and execute on the local Seattle team's main character for AI/ML storage solutions: focusing on AI/ML solutions, benchmarking, performance investigation and storage optimizations and client side products.Develop and enhance AI/ML client side solutions for storage.
Lead the team to design, develop and tune benchmarks for GCP Storage systems with the goal to make GCP Storage the best for AI/ML workloads.
Build deep technical expertise in file systems, operating systems, performance engineering, and the rapidly evolving AI/ML landscape.
Influence the industry and build credibility for GCP storage.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Google Cloud Storage’s mission is to provide the most trusted planet-scale storage system, with exceptional reliability, efficiency, performance, and simplicity.
The Storage AI/ML Solutions team leverages deep domain expertise to optimize Cloud Storage for AI/ML workloads at planet-scale. We empower customers to maximize GCP performance while assisting internal teams in positioning GCP Storage as the industry's leading solution. By engineering specialized AI client libraries and publishing credible benchmarks, the team provides metrics for throughput, latency, and scalability. Additionally, we actively collaborate with the open-source community to bridge technical gaps and ensure seamless integration with GCP.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Qualifications
Minimum qualifications: Bachelor’s degree or equivalent practical experience.8 years of experience with software development.
8 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years of experience in a people management or team leadership role. Experience with AI/ML, enterprise storage, or public cloud services.
Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
Experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, natural language processing, or other ML discipline. Experience in building and fostering a healthy and highly productive team in a rapidly changing technological ecosystem. Experience building infrastructure for models, diagnosis failures, and performance analysis.
Extended Qualifications
Bachelor’s degree or equivalent practical experience.8 years of experience with software development.
8 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years of experience in a people management or team leadership role. Experience with AI/ML, enterprise storage, or public cloud services.