Strong Data engineering fundamentals
- Utilize Big data frameworks like Spark/Databricks
- Training LLMs with structed and unstructured data sets.
- Understanding of Graph DB
- Experience with Azure Blob Storage, Azure Data Lakes, Azure Databricks
- Experience implementing Azure Machine Learning, Azure Computer Vision, Azure Video Indexer, Azure OpenAI models, Azure Media Services, Azure AI Search
- Determine effective data partitioning criteria
- Utilize data storage system spark to implement partition schemes
- Understanding core machine learning concepts and algorithms
- Familiarity with Cloud computing skills
- Strong programming skills in Python and experience with AI/ML frameworks.
- Proficiency in vector databases and embedding models for retrieval tasks.
- Expertise in integrating with AI agent frameworks.
- Experience with cloud AI services (Azure AI).
- Experience with GIS spatial data to create markers on maps ( lat long nearest topology of road, geo-locate between datasets, correlation etc.).
- Experience with Department of Transportation Data Domains developing an AI Composite Agentic Solution designed to identify and analyze data models, connect & correlate information to validate hypotheses, forecast, predict and recommend potential strategies and conduct What-if analysis.
- Bachelor's or master's degree in computer science, AI, Data Science, or a related field.