Machine Learning Engineer with Generative AI

Petadata - Las Vegas, NV

Full-time - Mid Level

Remote - Las Vegas, NV

About the position

The Machine Learning Engineer with Generative AI role focuses on developing advanced AI-driven solutions, particularly in the Azure ecosystem. This position is pivotal in creating a state-of-the-art chatbot using the Retrieval-Augmented Generation (RAG) technique to analyze customer reviews and develop an analytical dashboard powered by Azure OpenAI. The role aims to revolutionize customer interaction and data analysis methodologies through generative AI technologies.

Responsibilities

• Spearhead the creation of an advanced chatbot utilizing the RAG methodology to deliver nuanced interactions based on customer reviews.
• Architect and develop an analytical dashboard employing Azure OpenAI to unearth and present deep insights from complex datasets.
• Apply prompt engineering strategies to optimize the quality and relevance of generative AI outputs.
• Implement sophisticated sentiment analysis to understand emotional layers within customer feedback, refining the chatbot's empathetic engagement.

Requirements

• Proven expertise in integrating and leveraging Azure cloud services, with a strong emphasis on Azure Databricks and Azure OpenAI for generative AI applications.
• Exceptional skills in Python for AI development, complemented by expertise in using Spark for large-scale data processing and analytics.
• A robust foundation in machine learning principles and natural language processing, particularly in generative AI technologies and techniques.
• Demonstrated ability to design and operationalize scalable data pipelines within Databricks, optimized for generative AI workflows.

Nice-to-haves

• Creative problem-solving abilities, capable of translating intricate customer needs into tangible AI solutions.
• Exceptional analytical aptitude and meticulous attention to detail.

Benefits

• Professional work environment with opportunities for growth in the Information Technology field.