Generative AI Engineer

Job Information

Description

KPI Partners is seeking a highly skilled and experienced GenAI Engineer with a strong background in Data Engineering and Software Development to join our team. The ideal candidate will focus on enhancing our information retrieval and generation capabilities, with specific experience in Azure AI Search, data processing for RAG, and multimodal data integration and familiarity with Databricks.

Key Responsibilities:

• Design, develop, and optimize Retrieval-Augmented Generation models to improve information retrieval and generation processes within our applications.
• Develop and maintain search solutions using Azure AI Search to ensure efficient and accurate information access
• Process and prepare data to support RAG workflows, ensuring data quality and relevance.
• Integrate and manage various data types (e.g., text, images) to enhance retrieval and generation capabilities.
• Work closely with cross-functional teams to integrate data into our existing retrieval ecosystem, ensuring seamless functionality and performance.
• Ensure the scalability, reliability, and performance of data retrieval in production environments.
• Stay updated with the latest advancements in AI, ML, and data engineering to drive innovation and maintain a competitive edge.

What were looking for:

• Masters degree in Data Science or a related field is preferred.
• Approximately 3 years of experience in Data Science, MLOps, and Data Engineering
• Proven experience in AI and ML solution implementation, particularly in semiconductor manufacturing.
• Proficiency in Python
• Proven experience in data engineering and software development, with a focus on building and deploying RAG pipelines or similar information retrieval systems.
• Familiarity with processing multimodal data (e.g., text, images) for retrieval and generation tasks.
• Strong understanding of database systems (SQL and NoSQL) and data warehousing solutions.
• Proficiency in Azure AI, Databricks, and other relevant tools.

Python, RAG