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3 days ago
This role involves designing, developing, and deploying Generative AI applications using various tools. The successful candidate will build Retrieval-Augmented Generation (RAG) pipelines for enterprise AI applications, work on end-to-end projects, and integrate AI/ML search services.
Key Responsibilities:- Design and develop Generative AI applications using Python, FastAPI, Azure Durable Functions, and Azure OpenAI Services.
- Build RAG pipelines for enterprise AI applications.
- Work on end-to-end projects, including data ingestion, model integration, evaluation, and refinement.
- Integrate AI/ML search and data services such as Azure Cognitive Search, Cosmos DB, and other Azure-native tools.
- Automate key components of the RAG workflow and ensure production-grade performance and scalability.
- Evaluate, validate, and fine-tune the outputs of Generative AI models for accuracy and relevance.
- Implement monitoring, observability, and guardrails to ensure responsible and secure use of AI technologies.
- Collaborate with cross-functional teams to deliver innovative AI solutions.
- Strong programming experience in Python, including frameworks such as FastAPI and Flask.
- Deep understanding of Generative AI, machine learning, and RAG methodologies.
- Proficiency in Azure cloud services, especially Azure OpenAI, Functions, AI Search, and Cosmos DB.
- Hands-on experience with machine learning, deep learning, and natural language processing (NLP).
- Familiarity with ML/DL frameworks such as TensorFlow, PyTorch, and libraries like scikit-learn, spaCy, etc.
- Solid knowledge of machine learning algorithms including GPTs, CNNs, RNNs, k-NN, Naive Bayes, SVM, and Decision Forests.
- Experience in evaluating and fine-tuning LLM performance and implementing responsible AI practices.
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