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# AI Engineer

- **Company:** Rodriguez & Rodriguez Enterprises
- **Location:** St. Louis County, MO, United States
- **Salary:** $79,000.0 - $95,300.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Data Analysis, Bash Shell, Big Data, Extract Transform Load (ETL), Data Mining, Database Design, R (Programming Language), Apache Hadoop, Python (Programming Language), Linked Data, Unix Shell, Machine Learning, Natural Language Processing, Cloud Services, Tensorflow, SAS (Software), SQL Databases, Talend, Application Enhancement Tool, Apache Spark, Generative AI, Statistics Packages, Vba Programming Language, Data Analytics, Machine Learning Operations, Looker Analytics, Data Pipelines, Unsupervised Learning
- **Published:** October 22, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=45a2f923528fc1e2

## About the Role

* Experience with Python and SQL; familiarity with Java, C, R, SAS, VBA, or Bash (Unix shell) is useful.
 * Knowledge of TensorFlow and other machine learning frameworks, model training and evaluation, and model deployment.
 * Familiarity with Spark implementation, Talend, Looker, analytics, data analytics, statistical analysis tools, and machine learning cloud services.
 * Understanding of big data, scalability, and statistical analysis for research; quantum engineering experience is a plus.

## Description

* Prepare and transform data using ETL (extract, transform, load) workflows, data mining, and big data systems such as Hadoop and Spark.
 * Train, evaluate, and deploy AI models, including machine learning, unsupervised learning, predictive modeling, natural language processing, and generative AI applications.
 * Apply statistical modeling, statistical analysis, and machine learning/AI-based analysis to research and analytics needs.
 * Build and maintain scalable data pipelines, SQL databases, database designs, and linked data solutions; use cloud services such as AWS where appropriate.
 * Your impact: Delivering well-evaluated, scalable models helps teams make informed decisions and gives users more useful, dependable AI-powered tools.