Padmi

AI Specialist

United StatesPosted 1 month ago
Data Science And StatisticsUnspecified
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No restrictions on visa

AI Specialist is the title

In person interview however being a government organization it takes a while to get those set up

Location: onsite in Pontiac, MI

Duration: 6+ mo

The AI Specialist designs, develops, and deploys artificial intelligence and machine learning solutions to enhance business processes, improve decision-making, and drive innovation.

Collaborates with cross-functional teams to identify use cases, gather requirements, and implement AI-powered applications.

Responsible for data preprocessing, model selection, training, validation, and deployment.

Stays up-to-date with the latest AI research and industry trends to ensure the organization remains at the forefront of AI adoption.

Specifically:

The consultant should be able to create a solution that will enable law enforcement personnel and authorized users to query CLEMIS data using everyday language instead of complex SQL queries or traditional search interfaces

The consultant should have experience (at least 2-3 years' worth) with Public Safety applications like CAD, RMS and FRMS – should be able to fully understand the different datasets and their relationships

Initially we would expect the search to use current CLEMIS' search datasets

People (including aliases)

Identifiers

Incidents/Offenses

The future plan is to use the RMS (Records Management System) data for predictive analysis

Extract data from on premise Oracle/SQL Server DBs to AWS cloud

Transforms and if needed masks sensitive information (CJIS, PII, etc.)

Stores data in optimized formats for AI/ML workloads (in a Vector DB like PineCone)

Enables advanced RAG capabilities with AWS Bedrock

Use an industry standard AI Model like Claude or AWS Titan/Nova

We expect the entire solution to be hosted in the AWS Cloud

Experience Level: Senior

Environment: 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)

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