GenAI Engineer

Requirements:
•Approximately 8 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 and technologies.
•Excellent problem-solving skills and the ability to work independently and collaboratively in a team environment.
•Strong communication skills to effectively convey technical concepts to non-technical stakeholders.
•Experience in developing and deploying scalable ML models in production environments.
•Bachelor’s degree in Computer Science, Data Science, or a related field.
•Master’s degree in Data Science or a related field is preferred.

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 eco-system, 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