Cloud AI Engineer, Professional Services Organization, Google Cloud (English, Portuguese)

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 developed 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.

In this role, you will design and implement Machine Learning (ML) solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex Artificial Intelligence (AI). You will work with customers to identify opportunities to apply ML in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. You will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.

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: • Report and file issues against product, documentation and procedures by documenting desired behavior or steps to reproduce, and driving bugs to resolution. • Suggest code-level resolutions for complex product bugs by leveraging relevant tools and effective communication to all stakeholders internally and externally. • Resolve technical incidents and escalations by performing analysis utilizing relevant tools (e.g., SQL, R, Python) and leveraging custom data infrastructure or existing data models as appropriate, formulating and interpreting data to reach specific conclusions and next steps. • Identify opportunities and build solutions to improve support or empower customers to solve issues by using self-service tools and documentation.