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Cloud MLOps Architect

Role:

Cloud MLOps Architect

Location:

Pune - Baner, Pune - Viman Nagar, Chennai, Vadodara, Indore CITP, Remote

Experience:

9+ years

Key Skills:

AWS GCP, AWS Azure, AWS

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Cloud DevOps Architect As a Partner of Choice, Global Business Services (GBS) shapes our Global Business Services (GBS) center support Siemens’ companies worldwide to achieve excellence in their internal processes by providing smart and digital end-to-end solutions. We are a global powerhouse focusing on the areas of electrification, automation, and digitalization. One of the world’s largest producers of energy-efficient, resource-saving technologies, Siemens is a leading supplier of systems for power generation and transmission as well as medical diagnosis. In infrastructure and industry solutions the company plays a groundbreaking role. Who are we looking for? We are looking for an experienced Cloud Architect to join one of our Artificial Intelligence Team. Together with our Business Partners you will develop technology-driven cloud-based solutions. You will be engaged with Siemens Global Business Services, its customers and prospects across various business lines. You will work together with data science team to create AI assistants and be responsible for adapting all existing integrations. What role will you play? Act in the technical advisor with all the principals for cloud-native solutions, guiding teams through architectural decisions and ensuring best practices are followed Spearhead the development and implementation of our multi-cloud strategy, ensuring optimal resource utilization and cost efficiency Partner with business stakeholders, data teams, and application teams to align solutions with business goals and provide technical mentorship and governance on AI solutions architectures Champion DevOps practices across the teams/projects, building, maintaining, monitoring and optimizing AI/ML CI/CD pipelines that enable rapid and reliable software delivery Enable observability, performance tuning, model versioning, and rollback strategies Collaborate with data scientists to operationalize ML models in production and lead cloud solution architecture for

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