Software Engineer III, Machine Learning Infrastructure, Cloud AI
2 weeks ago
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years of experience with software development in Python, C++ or Java, or 1 year of experience with an advanced degree.
- Master's degree or PhD in Computer Science or a related technical field.
- 2 years of experience with data structures or algorithms.
- Experience with Generative AI, Large Language Models (LLM), or Machine Learning infrastructure, including model deployment, performance optimization, profiling, and debugging.
- Experience with distributed computing leveraging GPUs or TPUs, and cloud services in the areas of compute, storage, or networking.
- Ability to grow in a changing environment where Artificial Intelligence (AI) technologies are advancing.
- Ability to collaborate with cross-functional teams.
About the jobGoogle'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.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge 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
- Measure and optimize AI/ML model performance on Google Cloud infrastructure.
- Identify and resolve performance bottlenecks, collaborating 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 in-depth performance profiling, debugging, and troubleshooting of training and inference workloads, ensuring adherence to best practices through design and code reviews.
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