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Mid-level role, metro location, broad skillset, and known employer increase competition.
Specialized ML serving and hybrid cloud expertise limits cross-industry portability.
Explicit 5+ years plus mandatory ML, cloud, Kubernetes, and CI/CD requirements make filtering strict.
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Design and implement scalable, low-latency AI/ML model serving systems within a hybrid cloud environment.
Architect and manage hybrid cloud infrastructure combining on-premises and multiple cloud platforms (e.g., AWS, Azure, GCP) optimizing for performance and cost.
Lead deployment and versioning of AI/ML models including CI/CD pipeline setup, performance monitoring, security compliance, and collaboration with AI/ML teams.
Bachelor’s or Master’s degree in Computer Science or equivalent practical experience.
5+ years of software development and engineering experience with production system delivery.
Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch) and Python programming.
Experience in hybrid cloud architecture management and familiarity with containerization (Docker) and orchestration (Kubernetes).
Experienced in building large-scale AI/ML serving platforms integrating hybrid cloud infrastructure.
Proficient in DevOps practices including CI/CD pipelines and infrastructure as code for AI/ML systems.
Skilled at optimizing system performance, latency, and ensuring security and compliance for AI/ML production workflows.