Google Inc.
Software Engineering Manager, Workload Benchmarking, Google Cloud Platform Compu
Google Inc., Sunnyvale, California, United States, 94087
Overview
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 manage your project goals, contribute to product strategy and help develop your team. Teams work across areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, and user interface design; the list grows as the role evolves. 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. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services and Google Cloud. Our end users are Googlers, Cloud customers and billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do, including Google Cloud’s Vertex AI and related hyperscale computing initiatives. Responsibilities
Manage a team of 6-8 engineers, supporting new model benchmarking needs for customers. Identify and resolve technical bottlenecks to drive customer success. Understand state-of-the-art models and contribute to tooling for TPU/GPU inference and training. Partner with customers to optimize AI/ML model performance on Google Cloud infrastructure. Collaborate with internal infrastructure teams to enhance support for demanding AI workloads. Develop and deliver high-quality training materials and demos for customers and internal teams. Conduct design and code reviews to ensure adherence to best practices across technologies. Maintain and update documentation and educational content based on product changes and user feedback. Triage, debug, and resolve system issues by analyzing root causes and operational impact. Design and implement specialized machine learning solutions leveraging advanced ML infrastructure. Qualifications
Bachelor’s degree, or equivalent practical experience. 8 years of experience in software development. 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or compute technologies, storage or hardware architecture. 3 years of experience in a technical leadership role overseeing projects. 2 years of experience in a people management, supervision/team leadership role. Preferred qualifications
Master's degree or PhD in Computer Science or related technical field. 3 years of experience working in a structured organization. Experience with internal quality and repro testing to cover critical user journeys (CUJs). Ability to collaborate with internal infrastructure teams to identify bottlenecks and expand capacity as needed. Ability to drive continuous product improvement through bug fixes and short-term feature enhancements. Compensation and location
The US base salary range for this full-time position is $197,000-$291,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and other factors including job-related skills, experience, and 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 reflect base salary only and do not include bonus, equity, or benefits. Learn more about benefits at Google. Equal Opportunity
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. Google is a global company and English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
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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 manage your project goals, contribute to product strategy and help develop your team. Teams work across areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, and user interface design; the list grows as the role evolves. 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. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services and Google Cloud. Our end users are Googlers, Cloud customers and billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do, including Google Cloud’s Vertex AI and related hyperscale computing initiatives. Responsibilities
Manage a team of 6-8 engineers, supporting new model benchmarking needs for customers. Identify and resolve technical bottlenecks to drive customer success. Understand state-of-the-art models and contribute to tooling for TPU/GPU inference and training. Partner with customers to optimize AI/ML model performance on Google Cloud infrastructure. Collaborate with internal infrastructure teams to enhance support for demanding AI workloads. Develop and deliver high-quality training materials and demos for customers and internal teams. Conduct design and code reviews to ensure adherence to best practices across technologies. Maintain and update documentation and educational content based on product changes and user feedback. Triage, debug, and resolve system issues by analyzing root causes and operational impact. Design and implement specialized machine learning solutions leveraging advanced ML infrastructure. Qualifications
Bachelor’s degree, or equivalent practical experience. 8 years of experience in software development. 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or compute technologies, storage or hardware architecture. 3 years of experience in a technical leadership role overseeing projects. 2 years of experience in a people management, supervision/team leadership role. Preferred qualifications
Master's degree or PhD in Computer Science or related technical field. 3 years of experience working in a structured organization. Experience with internal quality and repro testing to cover critical user journeys (CUJs). Ability to collaborate with internal infrastructure teams to identify bottlenecks and expand capacity as needed. Ability to drive continuous product improvement through bug fixes and short-term feature enhancements. Compensation and location
The US base salary range for this full-time position is $197,000-$291,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and other factors including job-related skills, experience, and 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 reflect base salary only and do not include bonus, equity, or benefits. Learn more about benefits at Google. Equal Opportunity
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. Google is a global company and English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
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