Minimum qualifications:

　　Bachelor's degree in a technical field or equivalent practical experience.

　　6 years of experience in Artificial Intelligence applications such as deep learning, natural language processing, computer vision, or pattern recognition.

　　Experience in a statistical programming language (e.g. Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch).

　　Experience delivering technical presentations and leading business value sessions.

　　Preferred qualifications: Master's degree in Computer Science, Engineering, or a related technical field.

　　Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.

　　Experience designing and deploying with ML frameworks (e.g., TensorFlow, PyTorch, JAX, Spark ML, etc.).

　　Experience training and fine tuning models in large scale environments (e.g., image, language, recommendation) with accelerators.

　　Experience with distributed training and optimizing performance versus costs.

　　Experience with CI/CD solutions in the context of MLOps and LLMOps including automation with IaC (e.g., using Terraform).

　　About the job

　　The Google Cloud Platform team helps customers transform and build what's next for their business - all with technology built in the cloud. Our products are engineered for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers - developers, small and large businesses, educational institutions and government agencies - see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

　　In this role, you will identify, assess, and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. Along the way, you will work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings.

　　Google Cloud accelerates organizations' ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology - all on the cleanest cloud in the industry. 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

　　Be a trusted advisor to our top customers by understanding the customer's business process and goals. Architect AI-drive, spanning Data, AI, and Infrastructure, and work with peers to include the full cloud stack into overall architecture. Demonstrate how Google Cloud is differentiated by working with customers on POCs, demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues with training/serving models in a large scale environment. Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable other customers and internal teams. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements. Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement activities.