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Metro location plus broad AI/ML and MLOps skillset yields moderate candidate competition.
Specialized ML, LLM and MLOps experience required, moderately transferable across industries.
Multiple mandatory AI/ML, LLM, cloud and MLOps skills required, though no explicit years filter.
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Develop, test, and deploy AI/ML and Generative AI applications including LLM-based solutions, AI assistants, and workflow automation.
Build and maintain scalable AI solutions with APIs and backend services using Python, integrating AI applications with enterprise platforms.
Deploy and support AI solutions on cloud platforms (Azure, AWS, GCP), manage containerized applications with Docker and Kubernetes, and oversee data/model pipelines and monitoring.
Work Experience Required: Not explicitly mentioned in the JD.
Proficient in AI/ML frameworks, Generative AI, and software development with Python.
Experience deploying AI applications using cloud platforms such as Azure, AWS, or GCP.
Strong skills in containerization technologies like Docker and Kubernetes.
Experience building large language model (LLM) based AI solutions and automation workflows.
Comfortable working in cross-functional, Agile development teams involving engineering, product, and data stakeholders.
Strong software engineering fundamentals with a focus on clean, maintainable, and well-documented code in AI product development.