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Responsibilities Full Stack GCP Cloud Engineer
· Develop and design AI solutions which include components across Chatbots, Virtual Assistants, and Machine Learning
· Collaborate with peers across multiple technology disciplines ensuring AI platform and solutions deliver business and technical requirements
· Lead technical workshops in driving strategic initiatives, while developing and managing relationships both internal and external vendors
· Serve program teams to better understand their problems and goals, recommending possible solutions and building consensus around architecture
· Oversee and manage the full AI program life cycle implementations
· Assist, guide, and drive engineering teams by providing technical oversight during implementation and owning technical delivery
· · Ensure all architectural consideration and non-functional requirements around high availability, scalability, maintainability, and extensibilities are factored in in the core system.
· Implement POC, sample use case, and core platform components for a highly scalable application
Google Vertex AI, Google Big Query, Google DataPlex, Google Data Catalog, Cloud Functions, Cloud Composer, Kubernetes on Google, Networking and Firewall knowledge good to have
· Experience implementing, developing and deploying enterprise AI solutions involving Advanced Analytics, Machine Learning and Data Science specifically on Google Cloud ENvironment
· Experience with AI architecture and AI interface design covering diverse range of use cases and deployment models
· In-depth knowledge of components and architectural trade-offs across data management, governance, model building and production workflows of AI on GCP is a must
· Understand the workflow and planning pipeline architectures of ML and deep learning frameworks, with data, training/retraining and deployment
· Demonstrated expertise in modeling techniques with types of algorithm and development at least one of the following machine learning, deep learning, time-series, anomaly detection and prediction
· In-depth theoretical and practical knowledge in few select areas across AI cloud spectrum GCP AI/ML Services and MS Azure ML Services. Google cloud Certification is preferrable
· Knowledge and ability to apply OOPS concepts, SOLID principles, and design patterns.
· Experience with Computer Science fundamentals in data structures, algorithms, and complexity analysis
· Good Analytical skills.
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