Minimum qualifications:
- Bachelor's degree in Computer Science or Data Science, or equivalent practical experience.
- 6 years of experience working in AI/ML as a technical sales engineer or in software engineering.
- Experience delivering technical presentations and leading detailed business value sessions.
- Experience in python and Machine Learning (ML) frameworks (e.g., TensorFlow, PyTorch).
- Experience with Generative AI as a developer.
- Ability to communicate in English and Japanese fluently to interact with internal/external stakeholders.
Preferred qualifications:
- Google Cloud Platform (GCP) Professional with a certified Machine Learning Engineer.
- Experience architecting Machine Learning Operations (MLOps) systems in enterprise environments and in building, scaling, and optimizing enterprise-grade machine learning systems.
- Experience working with batch and online model serving with an understanding of model management and monitoring.
- Knowledge of vertex AI model deployment, and vertex pipelines, kubeflow, or MLFlow for automation and experimentation.
- Knowledge of GCP services and how to use them for analytics and data engineering, including BigQuery and Vertex AI.
- Excellent infrastructure building and maintenance skills on the GCP for data engineering pipelines.
About the job
As an AI/ML Field Solutions Architect, you will support Google Cloud Sales teams and engineering to incubate, pilot, and deploy Google Cloud’s industry leading Artificial Intelligence/Machine Learning (AI/ML) and generative artificial intelligence technology at AI natives and innovators, large enterprises, and early stage AI startups. You will help customers innovate faster with the solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators Tensor Processing Unit/Graphics Processing Unit (TPU/GPU).
In this role, you will identify, assess, and develop generative artificial intelligence 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 roadmaps 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. Along the way, 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 proof-of-concept, demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues with training/serving models in a global 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 path 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.