Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of coding experience in one or more of the following languages: C, C++, Java, or Python.
- 5 years of experience testing, maintaining, or launching software products.
- 5 years of experience with software development in one or more programming languages.
Preferred qualifications:
- Experience with architecture simulator development and microarchitecture.
- Experience with data structures or algorithms.
- Experience focused on ML algorithm and performance analysis and optimization.
- Experience with Large Language Models and ML frameworks and compilers.
- Knowledge of computer architecture such as TPU's or other accelerators.
- Excellent communication skills.
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 build the Machine Learning systems with Hardware and Software co-design and optimization.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
- Analyze performance, power, and energy efficiency of current and future Machine Learning workloads to identify issues.
- Enable the peak efficiency of future and current ML systems through full-stack ML hardware or software co-design by proposing hardware -aware algorithm optimization and related simulation modeling.
- Establish a understanding of the latest business-critical production ML models (e.g., large-language models, large embedding models) to inform optimizations of model architecture, software systems, and hardware architecture.
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 .
