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About the role
6+ years of hands-on experience in AI/ML engineering, with real-world deployment of models and pipelines. Strong expertise in Python Proven experience building and deploying LLM-based systems, particularly those using retrieval-augmented generation (RAG). Solid understanding of vector databases, embeddings, and semantic search architecture. Strong skills in data engineering: ETL pipelines, data cleaning, transformation, and large-scale processing. Experience in building REST APIs, containerizing services with Docker, and deploying to cloud infrastructure (preferably Azure or AWS). Strong understanding of cloud platforms and up-to-date data architectures (e.g., AWS, GCP, Azure). 6+ years of hands-on experience in AI/ML engineering, with real-world deployment of models and pipelines. Strong expertise in Python Proven experience building and deploying LLM-based systems, particularly those using retrieval-augmented generation (RAG). Solid understanding of vector databases, embeddings, and semantic search architecture. Strong skills in data engineering: ETL pipelines, data cleaning, transformation, and large-scale processing. Experience in building REST APIs, containerizing services with Docker, and deploying to cloud infrastructure (preferably Azure or AWS). Strong understanding of cloud platforms and up-to-date data architectures (e.g., AWS, GCP, Azure).
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