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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 we're looking for:
• Master's 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
Job ID: 150903611
Skills:
Git, Azure Functions, Python Programming, FastAPI, MongoDB, Kubernetes, agentic AI solutions, traditional AI algorithms, DevOps practices, AI development workflows, Redis Cache, vector databases, Jupyter Notebook, Relational Databases, ADLS, Azure services, CI CD pipelines, Generative AI LLMs
Skills:
BigQuery, Python, Cloud Functions, GenAI APIs, Vertex AI, Google Kubernetes Engine
Skills:
Azure Functions, Azure DevOps, LangChain, Entra ID, Prompt Flow, GPT-4o, ADLS Gen2, Azure Key Vault, Azure Blob Storage, AKS, Azure OpenAI, GPT-4o-mini, Azure Container Apps, Semantic Kernel, LangGraph, GitHub Actions, Azure AI Studio, Azure AI Search, Application Insights, Azure Monitor
Skills:
runway , Gcp, Azure, Python, AWS, LangChain, Veo, Speech TTS systems, CrewAI, vector search, LLMs, retrieval-augmented generation, Sora, diffusion-based audio models, GPT, Semantic Kernel, LangGraph, LoRA, Google ADK, Midjourney, Pika Labs, Runway ML, Stable Diffusion
Skills:
Machine Learning, Nlp, Pytorch, Cloud Technology, MLops, Python, AWS, Generative AI, Prompt engineering, Distributed training pipelines, Langchain, scikit-learn, LLMOps, Ai, Guardrails, LangGraph, LLM evaluation methodologies, LLM Agentic workflows, LLM technologies, Voice Conversational AI, LlamaIndex, Transformer architectures
