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 (ML) systems with hardware (HW) and software (SW) 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.
The US base salary range for this full-time position is $174,000-$252,000 + 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
- Analyze performance, power, and energy efficiency of current and future ML workloads to identify issues.
- Enable the peak efficiency of future and current ML systems through full-stack ML hardware-software co-design by proposing HW-aware algorithm optimization and related simulation modeling.
- Establish a deep 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.
- Explore and define future ML accelerator system and chip architectures with objective and data-driven insights.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 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.
Preferred qualifications:
- 5 years of experience with data structures and algorithms.
- Experience focused on ML algorithm and performance analysis and optimization.
- Experience with architecture simulator development and microarchitecture.
- Knowledge of computer architecture such as TPU's or other accelerators.
- Knowledge or experience with LLMs and ML frameworks and compilers.
- Excellent communication skills.