Posted:2 days ago|
Platform:
On-site
Full Time
• Configure, maintain, and optimize the Qdrant Vector Database for efficient entity search.
• Manage integration between UI layer (Streamlit chatbot), backend APIs, and Azure Data Lake.
• Create, monitor, and optimize Databricks jobs for data preparation and quality checks.
• Ensure smooth CI/CD deployment of models and applications using Bitbucket/Jenkins.
• Collaborate with Data Ops and Business teams for continuous data quality improvements.
• Troubleshoot and resolve production issues quickly, ensuring minimal downtime.
• Document processes and provide technical knowledge transfer to other team members.
• Hands-on experience building Retrieval-Augmented Generation pipelines
• OpenAI GPT API & Embedding models (Ada or similar)
• Prompt engineering and optimization techniques
• Data Engineering: Databricks, Azure Data Lake, PySpark, Pandas, NumPy.
• Vector Databases: Qdrant
• Web/UI Development: Streamlit or equivalent Python-based UI frameworks.
• Deployment & CI/CD: Docker, Bitbucket, Jenkins.
• API Development & Integration: REST API design and integration.
• Cloud & MLOps: Azure environment, model lifecycle management, performance tuning.
• Experience with multimodal RAG (text + image retrieval).
• Familiarity with model explainability tools.
• Knowledge of image processing libraries (OpenCV, PIL) if future scope includes images.
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