Vertex Ai Architect Hyderabad (India)

Role: Vertex AI architect Location: Hyderabad Shift Timings: 12:00 PM to 9:00 PM Experience: 10+ Years Roles and Responsibilities: Solution Architecture: Design end-to-end AI/ML pipelines on Vertex AI, from data ingestion and model training to evaluation and model serving. Hybrid Deployment Strategy: Architect and implement deployment pipelines that transition models developed in Vertex AI to on-premises, secure settings (utilizing technologies such as GKE Enterprise/Anthos or other container orchestration platforms). MLOps Implementation: Standardize CI/CD/CT (Continuous Training) workflows to manage model versioning, monitoring, and automated retraining loops. Infrastructure Optimization: Work closely with Infrastructure and Security teams to ensure on-premises environments are optimized for high-performance model serving, ensuring latency and throughput meet enterprise standards. Model Portability: Develop strategies for containerizing models (Docker/Kubernetes) to ensure consistent behavior across Google Cloud and on-premises environments. Cross-Functional Collaboration: Serve as a technical bridge between Data Scientists, Cloud Engineers, and On-Prem IT Ops to ensure seamless hand-offs and operational stability. Required Qualifications: Cloud Expertise: Proven experience with Google Cloud Platform, specifically the Vertex AI ecosystem (Vertex AI Pipelines, Feature Store, Model Registry, and Prediction services). Hybrid Cloud/On-Prem Experience: Demonstrated success in deploying cloud-trained models to on-premises, air-gapped, or hybrid infrastructure. Containerization Mastery: Expert-level knowledge of Docker and Kubernetes (GKE/Anthos/OpenShift). AI/ML Foundations: Robust proficiency in Python, TensorFlow/PyTorch, and general machine learning engineering practices. Infrastructure as Code (IaC): Hands-on experience with Terraform or similar tools for managing infrastructure across environments. Security & Compliance: Experience working in secure environme .