Customer Engineer I, AI Infrastructure, Google Cloud

• Be a trusted advisor to our customers, helping them understand and incorporate AI accelerators into their overall cloud strategy by recommending migration paths, integration strategies, and application architecture that incorporate Google Cloud AI optimized infrastructure.
• Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on proof of concepts, demonstrating features, optimizing model performance, profiling, and benchmarking.
• Build repeatable assets to enable other customers and internal teams.
• Influence Google Cloud strategy at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.
• Travel to customer sites and events as needed.

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 4 years of experience with cloud infrastructure.
• Experience building and operationalizing machine learning models.
• Experience in delivering technical presentations, leading discovery and planning sessions.

Preferred qualifications:

• Experience training and fine tuning large models (i.e., image, language, segmentation, recommendation, genomics) with accelerators.
• Experience with performance profiling tools (i.e., TensorFlow profiler, PyTorch profiler, Tensorboard).
• Experience designing/architecting large-scale infrastructure farms for specialist AI use cases.
• Experience with containerization, Kubernetes, Kubernetes on Google Cloud.
• Experience with machine learning benchmarks.
• Ability to engage with C-level or executive business leaders and influence decisions.

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 4 years of experience with cloud infrastructure.
• Experience building and operationalizing machine learning models.
• Experience in delivering technical presentations, leading discovery and planning sessions.