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Tier-1 employer, metro location, and popular AI engineering title increase candidate competition.
Requires specialized MLOps, PyTorch, and Azure expertise making cross-industry transfer limited.
Explicit 8+ years requirement plus mandatory MLOps, Azure, and PyTorch expertise enforces strict shortlisting.
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Develop and operate internal AI applications ensuring stability, security, and scalability on Azure Cloud.
Transition data science proof-of-concept models into production-ready AI solutions and maintain their reliable operation.
Establish AI application development standards, CI/CD pipelines, and operational best practices in a newly formed agile team.
8+ years of relevant software engineering experience with focus on AI application design, development, and operations.
Proficiency in Python and ML libraries such as PyTorch and scikit-learn.
Experience with AI/ML lifecycle including model deployment, monitoring, and scaling in production environments.
Hands-on development experience on Azure Cloud infrastructure and familiarity with security best practices for cloud environments.
Experienced in containerized microservices development using Docker and Azure Container Services for AI applications.
Skilled in building and maintaining CI/CD pipelines tailored for AI workloads and API integration.
Capable of collaborating effectively in small, agile, cross-functional teams to deliver production-grade AI solutions aligned with business goals.