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 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. 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.

Our Technical Solutions Engineers lead and own our large and important customer issues in addition to providing level two support to our other support teams. You will be a part of a global team that provides 24x7 support to help customers seamlessly make the switch to Google Cloud.

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. Our Technical Solutions team is driven by customers and 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

• Work with customers on their ML deployments to resolve issues and achieve production readiness and availability. Partner with Product and Engineering teams to improve products based on customer feedback.

• Manage customer problems through effective diagnosis, resolution, documentation/implementation of investigation tools to increase productivity for customer issues on Google Cloud Platform products.

• Develop an in-depth understanding of Google Cloud’s Artificial Intelligence/Machine Learning (AI/ML) products/solutions and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer-reported issues, building tools for faster diagnosis.

• Act as consultant and subject matter expert for internal stakeholders in engineering, sales, customer organizations to resolve technical deployment obstacles and improve Google Cloud.

• Work as part of team of engineers/consultants that globally ensure 24-hour customer support, including working non-standard work hours/shifts, and may include weekend work.

Minimum qualifications

• Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.

• 2 years of experience programming in a general purpose coding language or in system design, and troubleshooting and advocating for customers' needs, and triaging technical issues.

• 2 years of experience with 2 or more of the following: Web Tech, Data/Big Data, Systems Admin, Machine Learning, Networking, Kubernetes.

• Experience in Computer Networking (e.g., Firewalls, Routing, Load balancing, etc.), web technologies (e.g., HTTP, HTML, DNS, TCP, etc.), and artificial intelligence (AI) concepts and techniques.

Preferred qualifications

• 2 years of experience in recommendation systems, natural language processing, speech recognition, or computer vision.

• Experience troubleshooting ML models (e.g., Tensorflow, Keras, Py Torch).

• Experience working with public cloud services and infrastructure and working with networking/peering with private cloud.

• Experience with performance analysis of containerized systems and good understanding of underlying resources like Kubernetes, compute resources.

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