Minimum qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics or equivalent practical experience.
- 2 years of experience coding 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.).
- Experience in Artificial intelligence (AI) concepts and techniques.
Preferred qualifications:
- 2 years of experience in recommendation systems, natural language processing, speech recognition, or computer vision.
- Experience with performance analysis of containerized systems, good understanding of Kubernetes/compute resources.
- Experience with exploratory data analysis, model development and auxiliary practical concerns in production ML systems.
- Experience working on public cloud services and infrastructure and networking/peering with private cloud.
- Knowledge of Generative AI with understanding of Prompt Engineering, tokenization and troubleshooting ML models (e.g. Tensorflow, Keras, PyTorch).
- Excellent influencing skills in the application of AI/ML with the ability to lead design of AI-based solutions, web services, and debugging tools.
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 be a part of a global team that provides support for customer issues. 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'll help drive the success of Google Cloud by understanding and advocating for our customers’ issues. You will be required to work in a shift pattern or non-standard work hours as required. This may include weekend work.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.
- 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.
- Understand customer issues, advocate for their needs with internal teams, including product and engineering teams, to find ways to improve the product, fix product bugs and drive production.
- Manage customer problems through effective diagnosis, resolution, documentation, or implementation of investigation tools to increase productivity for customer issues on Google Cloud products.
- Develop an in-depth understanding of Google Cloud’s AI/ML products/solutions and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer issues, building faster diagnosis tools
- 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.
