Storage AI Specialist
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Job Description
Structured overview of role & requirementsAbout This Role
Design and build production-grade AI and Generative AI solutions using large language models (LLMs).
Develop AI agents, copilots, and workflow automation systems to improve user productivity and business outcomes.
Implement and manage Retrieval-Augmented Generation (RAG) architectures and optimize AI models for performance, safety, and cost in production environments.
Minimum Requirements
Bachelor's or master's degree in computer science, engineering, or closely related quantitative discipline.
6-9 years of relevant work experience in AI/ML development and deployment.
Proficiency in Python, SQL, Java, Go, AI/ML frameworks (PyTorch, Scikit-learn), and Generative AI technologies (GPT, Claude, Llama).
Experience with cloud platforms (AWS/Azure), Kubernetes, Docker, MLOps, CI/CD, and vector databases for RAG implementations.
Ideal Candidate Profile
Experienced in building scalable AI platforms supporting multiple AI products and teams with knowledge of MLOps and LLMOps.
Ability to drive innovation and experimentation with emerging AI technologies in hybrid cloud environments.
Familiarity with storage domain skills (Block/Object/File Storage) and GPU orchestration for model optimization and inference scaling.