Google
Overview
Software Engineer, TPU Performance – Google Responsibilities
Analyze performance, power, and energy efficiency of current and future ML workloads to identify issues. Enable the peak efficiency of future and current ML systems through full-stack ML hardware-software co-design by proposing hardware-aware algorithm optimization and related simulation modeling. Establish an understanding of the latest production ML models (e.g., large-language models, large embedding models) to inform optimizations of model architecture, software systems, and hardware architecture. Explore and define future ML accelerator system and chip architectures with objective and data-driven insights. Minimum qualifications
Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages. 2 years of coding experience in one or more of the following languages: C, C++, Java, or Python. 2 years of experience testing, maintaining, or launching software products. Preferred qualifications
2 years of experience with data structures/algorithms. Experience focused on ML algorithm and performance analysis and optimization. Experience with architecture simulator development and microarchitecture. Knowledge of computer architecture such as TPUs or other accelerators. Knowledge with LLMs and ML frameworks and compilers. Excellent communication skills. About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale and extend beyond web search. We look for engineers who bring fresh ideas from areas including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list grows every day. As a software engineer, you will work on a project critical to Google’s needs with opportunities to switch teams and projects as you grow and evolve. We value versatility, leadership qualities, and enthusiasm to tackle new problems across the full stack as we push technology forward. In this role, you will build ML systems with hardware and software co-design and optimization, and manage project priorities, deadlines, and deliverables. The MSCA (ML, Systems, and Cloud AI) organization designs, implements, and manages the hardware, software, ML, and systems infrastructure for Google services and Google Cloud. Our users are Googlers, Cloud customers, and billions of people who use Google services worldwide. We prioritize security, efficiency, and reliability across everything we do—from developing TPUs to running a global network—and drive toward the future of hyperscale computing, including Google Cloud’s Vertex AI and Gemini models for enterprise customers. The US base salary range for this full-time position is $141,000–$202,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location, with individual pay influenced by location and job-related skills and experience. Your recruiter can share more about the specific range for your location during the hiring process. Compensation details listed reflect base salary only and do not include bonus, equity, or benefits. Equal opportunity
Google is proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See Google’s EEO Policy and EEO is the Law. If you require accommodations, please let us know by completing the Accommodations for Applicants form.
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Software Engineer, TPU Performance – Google Responsibilities
Analyze performance, power, and energy efficiency of current and future ML workloads to identify issues. Enable the peak efficiency of future and current ML systems through full-stack ML hardware-software co-design by proposing hardware-aware algorithm optimization and related simulation modeling. Establish an understanding of the latest production ML models (e.g., large-language models, large embedding models) to inform optimizations of model architecture, software systems, and hardware architecture. Explore and define future ML accelerator system and chip architectures with objective and data-driven insights. Minimum qualifications
Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages. 2 years of coding experience in one or more of the following languages: C, C++, Java, or Python. 2 years of experience testing, maintaining, or launching software products. Preferred qualifications
2 years of experience with data structures/algorithms. Experience focused on ML algorithm and performance analysis and optimization. Experience with architecture simulator development and microarchitecture. Knowledge of computer architecture such as TPUs or other accelerators. Knowledge with LLMs and ML frameworks and compilers. Excellent communication skills. About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale and extend beyond web search. We look for engineers who bring fresh ideas from areas including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list grows every day. As a software engineer, you will work on a project critical to Google’s needs with opportunities to switch teams and projects as you grow and evolve. We value versatility, leadership qualities, and enthusiasm to tackle new problems across the full stack as we push technology forward. In this role, you will build ML systems with hardware and software co-design and optimization, and manage project priorities, deadlines, and deliverables. The MSCA (ML, Systems, and Cloud AI) organization designs, implements, and manages the hardware, software, ML, and systems infrastructure for Google services and Google Cloud. Our users are Googlers, Cloud customers, and billions of people who use Google services worldwide. We prioritize security, efficiency, and reliability across everything we do—from developing TPUs to running a global network—and drive toward the future of hyperscale computing, including Google Cloud’s Vertex AI and Gemini models for enterprise customers. The US base salary range for this full-time position is $141,000–$202,000 plus bonus, equity, and benefits. Salary ranges are determined by role, level, and location, with individual pay influenced by location and job-related skills and experience. Your recruiter can share more about the specific range for your location during the hiring process. Compensation details listed reflect base salary only and do not include bonus, equity, or benefits. Equal opportunity
Google is proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See Google’s EEO Policy and EEO is the Law. If you require accommodations, please let us know by completing the Accommodations for Applicants form.
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