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.

As a Technical Solutions Engineer, you will own important customer issues and provide level two support to other support teams. In this role, you will be part of a global team that provides 24x7 support to help customers seamlessly make the switch to Google Cloud.

You will troubleshoot technical problems for customers using a mix of debugging, networking, system administration, updating documentation, and when needed, coding or scripting. You will make products easier to adopt and use by making improvements to the product, tools, processes, and documentation. As the Technical Solutions team is driven by customers, you will help drive the success of Google Cloud by understanding and advocating for 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.

The US base salary range for this full-time position is $150,000-$218,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Collaborate with customers on ML deployments to resolve issues and achieve production, availability, and scale while partnering 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 understanding of Google Cloud’s AI and ML products or solutions and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer-reported issues and building tools for faster diagnosis.

• Serve as a consultant and SME for internal stakeholders in engineering, sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud.

• Work as part of a team of engineers or consultants that ensure 24-hour customer support, including working non-standard work hours or shifts and possibly including weekends.

Minimum qualifications

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

• 6 years of experience with two or more of the following: web technology, data/big data, systems administration, machine learning, networking, kubernetes.

• Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C, or C++) including data structures and algorithms, and software design.

• Experience with AI model training, performance analysis, and integration with other cloud services supporting customer projects to completion.

• Experience in computer networking (e.g., firewalls, routing, load balancing, etc.), web technologies (e.g., HTTP, HTML, DNS, TCP, etc.), and AI concepts and techniques.

Preferred qualifications

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

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

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

• Knowledge of data warehousing concepts, data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, etc.).

• Ability to recommend ML best practices for practical business use.

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