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AI Infrastructure Solutions Architect
2 months ago
Minimum qualifications:
Bachelor's degree in Computer Science, Mathematics, or a related technical discipline, or equivalent practical experience. A minimum of 5 years of experience with cloud infrastructure, including knowledge of hardware configurations, auto-scaling, and auto-provisioning. Proficiency in programming languages such as Python and bash scripting, along with experience using open-source frameworks like TensorFlow, PyTorch, and Jax.
Experience in distributed training and optimizing performance relative to costs is essential. Familiarity with orchestrators such as Slurm and Kubernetes is required. Proven experience in building and operationalizing machine learning models is also necessary.
Preferred qualifications:
Experience in training and fine-tuning large models (e.g., image, language, segmentation, recommendation, genomics) utilizing accelerators. Knowledge of performance profiling tools (e.g., TensorFlow profiler, PyTorch profiler, Tensorboard) is advantageous. Experience in running Machine Learning Performance benchmarks is preferred. Skills in designing and architecting large-scale AI compute clusters are desirable. Familiarity with containerization and Kubernetes on cloud platforms is beneficial. The ability to debug distributed training and inference code is important.
About the role: As an AI Infrastructure Solutions Architect, you will collaborate with Google Cloud sales teams to incubate, pilot, and deploy industry-leading AI/ML accelerators (TPU/GPU) for AI innovators, large enterprises, and emerging AI startups.
Your role will involve assisting customers in accelerating innovation through solutions that leverage Google Cloud's flexible and open infrastructure. You will identify and evaluate large-scale AI opportunities that can benefit from AI-optimized infrastructure.
Your responsibilities will include helping customers integrate accelerators into their overall cloud strategy by conducting benchmarks for existing models, identifying opportunities for new models, developing migration strategies, and analyzing cost-to-performance ratios.
Throughout this process, you will work closely with internal Cloud AI teams to eliminate obstacles and shape the future of our offerings. Google Cloud empowers organizations to digitally transform their business and industry. We provide enterprise-grade solutions that utilize Google's cutting-edge technology and tools to support sustainable development.
Customers across more than 200 countries and territories rely on Google Cloud as their trusted partner to foster growth and address their most pressing business challenges.
Responsibilities: Serve as a trusted advisor to our key customers, guiding them in understanding and incorporating AI accelerators into their overall cloud strategy by designing large-scale training and inference platforms that utilize the latest accelerators offered by Google Cloud.
Showcase how Google Cloud stands out by highlighting the capabilities of accelerators through collaboration with customers on proof of concepts, demonstrating features, optimizing model performance, profiling, and benchmarking.
Develop repeatable assets to empower other customers and internal teams. Advocate for enterprise customer requirements to influence Google Cloud strategy at the intersection of infrastructure and AI/ML. Travel to customer sites and events as necessary.
