Minimum qualifications:

　　Bachelor's degree in Science, Technology, Engineering, Math, or equivalent practical experience.

　　Experience programming or debugging code in one or more of the following: Python, Java, C, C++, .NET, Shell, Perl, JavaScript.

　　Experience with ML frameworks such as TensorFlow, Pytorch and Scikit-learn.

　　Experience working with enterprise customers in a support, implementation, or solution design capacity.

　　Preferred qualifications: Experience in Machine Learning (ML), recommendation systems, natural language processing, speech recognition, or computer vision.

　　Experience in production deployment of machine learning.

　　Experience developing and/or training models using machine learning technologies (e.g., Tensorflow, Keras, PyTorch).

　　Experience with machine learning architectures (e.g., AlexNet, LSTM, Conformers, BERT, etc.).

　　Experience with exploratory data analysis, model development and auxiliary practical concerns in production ML systems.

　　Excellent leadership and influencing skills in the application of AI or Machine Learning, with the ability to lead the design and implementation of AI-based solutions, web services, and debugging tools.

　　About the job

　　As an Executive Cloud Technical Solutions Engineer, you will be a part of a global team that provides 24x7 support to help customers seamlessly make the switch to Google Cloud. You will ensure that we have the necessary tools, processes and needed technical knowledge to resolve the issue.

　　In this role, you will troubleshoot technical problems for customers with a mix of debugging, networking, system administration, updating documentation, and when needed, coding/scripting. You will focus on AI/ML products within Google Cloud. You will make our products easier to adopt and use by making improvements to the product, tools, processes and documentation. You will help drive the success of Google Cloud by understanding and advocating for our customers' issues. You will work non-standard hours, including weekends, holidays, and on shift-based schedules as needed.

　　Responsibilities

　　Manage customer problem through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on Google Cloud Platform products, including AI/ML products on Google Cloud Platform (GCP). Act as a consultant and subject matter expert for internal stakeholders in engineering, sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud. Understand customer issues and advocate for their needs with cross-functional teams, including product and engineering teams, to find ways to improve the product, and drive high-quality production. Develop an understanding of Google's product technology and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer reported issues, and building tools for faster diagnosis.

　　Work as part of a team of engineers/consultants that globally ensure 24 hour customer support.