Minimum qualifications:Bachelor's degree or equivalent practical experience. 8 years of experience in software development, and with data structures/algorithms. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience in the Machine Learning field.5 years of experience with performance, large scale systems data analysis, visualization tools, or debugging.Experience with distributed systems.Preferred qualifications:Master's degree or PhD in Computer Engineering, Electrical Engineering, or Computer Science, or a related field.Experience with large-scale distributed systems, computer architecture, networking, related software infrastructure including low level performance analysis, memory/storage systems, ML/AI methods.Knowledge of concurrency, parallelism, synchronization, consistency, events, scheduling, communications, and overhead in software and hardware systems.Knowledge of silicon architecture and design with the ability to root cause performance bottlenecks.Expertise in any of the following: Operating Systems, Networking systems, Storage systems, Analytics, Machine Learning, working with distributed query processing and deep functional flows. 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 well beyond web search. We're looking for engineers who bring fresh ideas from all 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 goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.In this role, you will have the opportunity to blend software design practices and the modeling, and performance analysis works that informs the system architecture and design of Google systems, help solve complex problems including but not limited to hardware acceleration, performance bottlenecks, system hierarchies, concurrency, computer organization, automation, and machine learning. You will leverage Generative AI (Gen AI) techniques to transform the way software development and performance optimization is conducted in the industry.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 $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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. Responsibilities Manage performance analysis and Machine Learning compiler experience.Integrate AI/ML methods in Software engineering developer workflows.Manage Large Language Models (LLMs), transformer architecture, and distributed systems.Drive fleet operation and management, and system reliability.Drive new methodologies for improved Software Engineering and Productivity experience.
