Minimum qualifications:
- Bachelor's degree in Computer Science, Data Science, or equivalent practical experience.
- 6 years of experience in Artificial Intelligence/Machine Learning (AI/ML) as a technical business engineer or in software engineering.
- Experience in Python and Machine Learning (ML) frameworks (e.g., TensorFlow, PyTorch).
- Experience in delivering technical presentations and leading detailed business value sessions.
- Experience in developing Generative AI.
- Certification in Google Cloud Platform (GCP) Professional Machine Learning Engineer.
- Experience in architecting Machine Learning Operations (MLOps) systems in enterprise environments with building, scaling, and optimizing Machine Learning systems.
- Experience with batch and online model serving with the knowledge of model management and monitoring
- Knowledge of Google Cloud Platform (GCP) services and how to use them for problem solving and data engineering, including BigQuery and Vertex AI.
- Knowledge of Vertex AI model deployment with Vertex Pipelines, model deployment, Kubeflow or MLFlow for automation.
- Excellent infrastructure building and maintenance skills for data engineering pipelines.
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About the job
In this role, you will identify, assess, and develop Generative AI (GenAI) and Artificial Intelligence/Machine Learning (AI/ML) applications by applying 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 with internal Cloud AI teams to remove roadblocks and shape the future of our offerings. You will need to be able to navigate ambiguity, troubleshoot and find solutions, and learn quickly in a changing technology space. You will also need to possess excellent customer-facing communication skills.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 objectives. Architect AI-drive, spanning Data, Artificial Intelligence (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 demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues training/serving models.
- Build 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 Artificial Intelligence/Machine Learning (AI/ML) by advocating for enterprise customer requirements.
- Coordinate regional field enablement with leadership and work with product and partner organizations on external enablement activities.
- Travel as needed.