Software Engineer II, TPU Compiler
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 1 year of experience with data structures or algorithms.
- Experience with C++, compiler construction and performance optimization.
Preferred qualifications:
- Master's degree in Computer Science or a related technical field.
- Experience with Machine Learning architecture and infrastructure.
- Understanding of accelerators, for example, VLIW, Vector machines, GPUs or DSPs.
- Understanding of debugging correctness and performance issues at all levels of the stack.
About the job
The AI and Infrastructure team works on the world’s toughest problems, redefining what’s possible and the possible easy. We empower Google customers by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Googler Cloud customers, and billions of Google users worldwide. We’re at the center of amazing work at Google by being the “flywheel” that enables our advanced AI models, delivers computing power across global services, and offers platforms that developers use to build services.
In AI and Infrastructure, we shape the future of hyperscale computing by inventing and creating world-leading future technology, and drive global impact by contributing to Google infrastructure, from software to hardware (including building Vertex AI for Google Cloud). We work on complex technologies at a global scale with key players in the AI and systems space. Join a team of talented individuals who not only work together to keep data centers operating efficiently but also create a legacy of driving innovation by building some of the most complex systems technologies.
The TPU Backend and NPI team is at the crux of Machine learning, Compilers and TPU hardware. We collaborate with teams across hardware and software, and enable Google to have the industry's most performant machine learning chip (TPU) at the hands of machine learning (ML) modeling teams. The vast majority of all machine learning at Google flows through tools that the TPU backend and NPI team is creating, so impact is both immediate and massive. Enable a novel processor to accelerate machine learning workloads. This hardware will be deployed at scale and will power some of Google's most critical production workloads. Opportunities include performance optimization, programmability, usability and co-design of next generation hardware.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
- Write product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- 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.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Contribute to the TPU compiler for a novel processor designed to accelerate machine learning workloads. Target and compile high-performance implementations of operations at a distributed scale.
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