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Strong employer brand, mid-level generalist title, metro location, and broad skillset increase candidate competition.
Specialized ML platform and hybrid cloud expertise limit cross-industry transferability.
Explicit 5+ years and mandatory ML, cloud, and Kubernetes skills make shortlisting highly strict.
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Design and implement scalable AI/ML serving systems capable of low latency and handling varying loads across hybrid cloud environments.
Architect and manage hybrid cloud infrastructure integrating on-premises and multiple cloud platforms optimizing performance, cost, and scalability.
Oversee deployment, versioning, and CI/CD pipelines for AI/ML models in production, including performance monitoring and security compliance.
Bachelor's or Master's degree in Computer Science or equivalent practical experience.
5+ years of experience in software development and engineering with delivery of production systems.
Hands-on experience with AI/ML frameworks such as TensorFlow or PyTorch and strong Python programming skills.
Experience with hybrid cloud architectures, containerization (Docker), orchestration tools (Kubernetes), and DevOps practices (CI/CD).
Experienced in architecting and managing complex AI/ML platforms within hybrid cloud environments, including multiple cloud providers.
Proficient in deploying and maintaining AI/ML models in production with performance optimization and security compliance focus.
Capable of collaboration with interdisciplinary teams (AI/ML researchers, data engineers) to translate research into production-grade systems.