PRACYVA
GenAI Python Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI Python Engineer with a contract length of "unknown," offering a pay rate of "unknown." Required skills include AI/ML engineering, document parsing, SQL/NoSQL experience, and strong Python programming. Experience with Generative AI and RAG applications is essential.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
July 11, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Sheffield, England, United Kingdom
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Datasets #Data Extraction #Scala #Python #HBase #NoSQL #Databases #Programming #ML (Machine Learning) #Data Integration #"ETL (Extract #Transform #Load)" #SQL (Structured Query Language)
Role description
Strong experience in AI/ML engineering, with hands-on exposure to Generative AI use cases.
Experience in building RAG applications in enterprise environments.
Strong knowledge of document parsing, OCR, and image-based data extraction.
Experience with LLM orchestration frameworks and prompt design.
Experience with vector databases and semantic search.
Very Strong programming skills in Python.
Experience working with SQL/NoSQL databases and enterprise data integration patterns.
Understanding of evaluation frameworks for GenAI systems using benchmark datasets and ground-truth-based validation.
Experience in building scalable APIs/services and production-grade AI workflows.
Strong experience in AI/ML engineering, with hands-on exposure to Generative AI use cases.
Experience in building RAG applications in enterprise environments.
Strong knowledge of document parsing, OCR, and image-based data extraction.
Experience with LLM orchestration frameworks and prompt design.
Experience with vector databases and semantic search.
Very Strong programming skills in Python.
Experience working with SQL/NoSQL databases and enterprise data integration patterns.
Understanding of evaluation frameworks for GenAI systems using benchmark datasets and ground-truth-based validation.
Experience in building scalable APIs/services and production-grade AI workflows.
