Software Engineer II, AI and Machine Learning, Cloud AI Infrastructure

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).
  

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 1 year of experience with ML infrastructure or performance.
• Experience in cloud services such as Compute, Storage, and Networking.

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. 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

• Measure and optimize AI/ML model performance on Google Cloud infrastructure.
• Identify and resolve performance issues and collaborate with internal infrastructure teams to enhance support for demanding AI workloads as needed.
• Develop and deliver high-quality training and demos for both customers and internal teams.
• Contribute to ongoing product improvement by identifying bugs, recommending enhancements, and writing and testing production-quality code.
• Conduct performance profiling, debugging, and troubleshooting of training and inference workloads, ensuring adherence to best practices through design and code reviews.