Minimum qualifications:

Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.

Candidates will typically have 8 years of experience in technical project management, stakeholder management, solution engineering or technical consulting, and 4 years of experience in technical leadership.

Typically 2 years of experience with statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch).

Typically 1 year of experience in technical troubleshooting.

Experience in AI applications (e.g., deep learning, NLP, computer vision, or pattern recognition).

Ability to communicate in English and German fluently to support English and German speaking clients.

Preferred qualifications:

Master's degree in Computer Science, Engineering, or a related technical field.

Experience designing and deploying with one or more from the following ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.

Experience training and fine tuning models in large scale environments (e.g., image, language, recommendation) with accelerators.

Experience with distributed training and optimizing performance versus costs.

Experience with CI/CD solutions in the context of MLOps and LLMOps including automation with IaC (e.g., using terraform).

Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.

About the job
As a Generative AI Field Solutions Architect, you will support Google Cloud Sales and Engineering teams to incubate, pilot, and deploy Google Cloud's industry leading AI/ML and Generative AI technology with AI natives, large enterprises, and early-stage AI startups. You will help customers innovate faster with solutions using Google Cloud's flexible and open infrastructure including AI Accelerators (TPU/GPU).
In this role, you will identify, assess and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. You will work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings. You will navigate ambiguity, troubleshoot and find solutions, and learn quickly in a rapidly changing technology space.
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 trusted advisor to our customers by understanding the customer's business process and objectives. Architect AI-drive, spanning Data, AI, and Infrastructure, and work with peers to include the full cloud stack into overall architecture.

Demonstrate how Google Cloud is differentiated by working with customers on POCs, demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues training/serving models in a large-scale environment.

Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable other customers and internal teams. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.

Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement activities. Travel as needed.

Field Solutions Architect, Generative AI, Google Cloud