Software Engineer III, Performance, AI Platforms

Google•Apply•Published 25 days ago•First seen 25 days ago

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.

The Platforms AI-augmented Compute Efficiency (ACE) team is dedicated to addressing the affordability gap through focused efforts on scaling, adapting, and simplifying software-hardware interfaces amidst the swift evolution of customer demands. Our mission is to collaboratively enhance the efficiency, performance, reliability, and resilience of new compute platforms—including Central Processing Units (CPUs), Tensor Processing Units (TPUs), and Graphics Processing Units (GPUs) ensuring these innovations are effectively aligned with the urgent needs of our Cloud and Machine Learning fleets.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

The US base salary range for this full-time position is $141,000-$202,000 + 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.

Responsibilities

Enhance the efficiency, performance, reliability, and corruption resilience of new compute platforms such as CPUs, TPUs, and GPUs, ensuring these innovations are effectively aligned with the urgent needs of our Cloud and Machine Learning fleets.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Write product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.

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 experience with performance, large-scale systems data analysis, visualization tools, or debugging.
2 years of experience with computer architecture, performance analysis, and performance modeling.
Experience in performance analysis and optimization for compute platforms such as CPUs, TPUs, and GPUs.

Preferred qualifications:

Master's degree or PhD in Computer Science or a related technical field.
Experience in microarchitectures, reliability and performance programming, and multi-thread/multi-core programming.
Experience in architecture analysis and optimization (including system architecture and performance modeling), machine learning system theory, TensorFlow, and compiler optimizations.
Understanding of low-level performance, memory/storage systems, and concurrent programming techniques for addressing performance and reliability issues.