Responsibilities:
- Design, develop, and deploy solutions to enhance business processes and decision-making.
- Manage data preprocessing, model selection, training, validation, and final deployment.
- Partner with teams to identify use cases and gather functional requirements for AI-powered applications.
- Stay current with AI research and industry trends to maintain the organization’s competitive edge.
- Create a solution allowing law enforcement and authorized users to query CLEMIS (Courts and Law Enforcement Management Information System) data using everyday language instead of complex SQL or legacy interfaces.
- Implement search capabilities for People: Including known aliases; Identifiers: Specific person-based markers; Incidents/Offenses: Historical and active records.
- Predictive Analysis: Develop a roadmap to utilize Records Management System (RMS) data for future predictive modeling.
- Extract data from on-premise Oracle and SQL Server databases into the AWS Cloud environment.
- Transform and mask sensitive information, ensuring strict adherence to CJIS and PII standards.
- Store data in optimized formats for ML workloads (utilizing Vector Databases like Pinecone).
- Enable advanced Retrieval-Augmented Generation (RAG) capabilities using AWS Bedrock.
- Deploy industry-standard models such as Claude or AWS Titan/Nova.
Experience:
- 2–3 years of experience with Public Safety applications, specifically CAD, RMS, and FRMS.
- Deep understanding of public safety datasets and their complex interrelationships.
- Experience with Python, R, TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Databricks, Jupyter Notebooks, AWS (SageMaker, EC2, S3), Azure (Machine Learning Studio, Databricks), SQL, NoSQL databases, data visualization tools (Tableau, PowerBI)