Google's software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information. The ML, Systems, and Cloud AI (MSCA) organization designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services and Google Cloud, prioritizing security, efficiency, and reliability to shape the future of hyperscale computing.
Requirements
- 2 years of experience with software development in one or more programming languages.
- 2 years of experience with computer architecture, performance analysis, and performance modeling.
- 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
- Experience working with Graphics Processing Unit (GPU) or Tensor Processing Unit (TPU).
- 2 years of experience with data structures or algorithms.
- Experience with machine learning, compiler optimization, code generation, and runtime systems for GPU architectures.
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).
- 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.
Other
- Bachelor’s degree or equivalent practical experience.
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Understanding of modern GPU architectures (e.g., NVIDIA, AMD), memory hierarchies, and performance bottlenecks.
- Google is proud to be an equal opportunity workplace and is an affirmative action employer.
