About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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

• Partner with customers to measure Artificial Intelligence/Machine Learning (AI/ML) model performance on Google Cloud infrastructure. Identify and resolve technical bottlenecks to drive customer success.

• Collaborate with internal infrastructure teams to enhance support for demanding AI workloads. Develop and deliver quality training materials and demos for customers and internal teams.

• Contribute to product improvement by identifying bugs and recommending enhancements. Write and test production-quality code for system development and deployment.

• Conduct performance profiling, debugging, and troubleshooting of training and inference workloads. Conduct design and code reviews to ensure adherence to best practices across technologies.

• Triage, debug, and resolve system issues by analyzing root causes and operational impact. Design and implement specialized ML solutions, leveraging advanced ML infrastructure.

Minimum qualifications

• Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.

• 5 years of experience in software development using one or more programming languages.

• 2 years of experience with ML infrastructure, including model deployment, evaluation, data processing, and debugging.

• 1 year of experience in ML performance, large-scale systems data analysis, ML debugging, Large Language Models (LLMs), or a related area within ML.

Preferred qualifications

• Master’s degree or PhD in Computer Science or a related technical field.

• Experience with data structures and algorithm.

• Ability to develop advanced (e.g., Level 400) AI/ML infrastructure training materials and demos.