Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
- Experience in C++.
- Experience with performance, systems data analysis, visualization tools, or debugging.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 5 years of experience with data structures and algorithms.
- Experience in Machine Learning and High Performance Computing (HPC).
- Experience optimizing distributed programs at large-scale and experience with compilers and compiler construction.
- Excellent debugging and programming concurrent/parallel computations, while working on accelerators including but not limited to VLIW and vector machines, GPUs, or DSPs.
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 manage information at a 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.
In this role, you will develops the Accelerated Linear Algebra (XLA) Tensor Processing Units (TPU) parallelizing compiler used to partition, optimize, and run large-scale machine learning models across multiple TPU accelerators for internal Google, Google DeepMind and external customers. You will work on the software stack that includes the partitioner to share work across multiple TPUs, scheduling optimizations, and code generation.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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.Responsibilities
- Write product or system development code for the TPU compiler (in C++).
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Contribute to a compiler which scales-out machine learning models across accelerators like TPU/Graphics Processing Unit (GPU) at Google and Cloud.
- Conduct static and runtime performance analysis of important large-scale production models.
- Design and implement performance optimizations and critical features, which increase the velocity of important production teams.
Google is proud to be an equal opportunity workplace and is 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 also
Google's EEO Policy and
EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our
Accommodations for Applicants form.
