Software Engineer II, AI/ML, Technical Infrastructure
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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 collaborating with customers and field teams.
- 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.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
- Collaborate with customers to measure and optimize their AI/ML model performance on Google Cloud infrastructure.
- Identify and resolve performance issues to ensure customer success, 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 performance profiling, debugging, and troubleshooting of training and inference workloads, ensuring adherence to best practices through design and code reviews.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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