Customer Engineer, AI Infrastructure

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.

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 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 bench-marking.
• 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.
• Be responsible for business growth and workload acceleration on AI infrastructure products and solutions for Google Cloud Platform (GCP).

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 6 years of experience with cloud native architecture in a customer-facing or support role.
• 5 years of experience with cloud infrastructure.
• 5 years of experience in a technical role focused on AI infrastructure, GPU programming (e.g., CUDA, OpenCL) and optimization techniques.
• Experience building and operationalizing machine learning models.

Preferred qualifications:

• Experience training and fine-tuning large models (e.g., image, language, segmentation, recommendation, genomics) with accelerators.
• Experience with performance profiling tools (e.g., TensorFlow profiler, PyTorch profiler, Tensorboard).
• Experience designing/architecting large-scale infrastructure farms for specialist Artificial Intelligence (AI) use cases.
• Experience with running Machine Learning (ML) Perf benchmarks, distributed training and optimizing performance versus costs.
• Experience with High Performance Computing (HPC) environments and contributions to open-source projects related to AI or infrastructure.
• Excellent communication, presentation, and teamwork skills.