Cloud Technical Solutions Engineer, Data, AI/ML

Minimum qualifications:

• Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  
• 4 years of experience programming or debugging code in Python, Java, C, C++, .NET, Shell, Perl, or JavaScript.
  
• 4 years of experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
  
• Ability to work non-standard hours and differing rotations/shifts.
  

Preferred qualifications:

• 2 years of experience in machine learning, recommendation systems, natural language processing, speech recognition, or computer vision, and production deployment of machine learning.
  
• Experience developing and/or training models using machine learning technologies (e.g., Tensorflow, Keras, PyTorch).
  
• Experience with exploratory data analysis, model development, and auxiliary practical concerns in production ML systems.
  
• Experience with specific machine learning architectures (e.g., AlexNet, LSTM, Conformers, BERT, etc.).
  
• Effective leadership and influencing skills in the application of AI or Machine Learning, with capacity to lead the design and implementation of AI-based solutions, web services, debugging tools.
  

About the job

As a Technical Solutions Engineer, you will be a part of a global team that provides support to help customers make the switch to Google Cloud. You will ensure 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 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.

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

• Be a thought leader in ML operations helping customers proactively. Work with immediate teams to increase operational efficiency and improve product supportability.
• Work with customers on their production ML deployments to resolve issues and achieve production readiness, availability, and scale. Partner with Product and Engineering teams to improve products based on customer feedback.
• Manage customer problems through effective diagnosis, resolution, documentation, or implementation of investigation tools to increase productivity for customer issues on Google Cloud Platform products.
• Develop an in-depth understanding of Google Cloud’s AI/ML products/solutions and underlying architectures by troubleshooting, reproducing, determining the root cause for customer reported issues, and building tools for faster diagnosis.
• Act as consultant and subject matter expert for internal stakeholders in engineering, sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud.