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# Senior AI/ML Engineer

- **Company:** Thornton Tomasetti
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $95,000.0 - $125,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Simulation, Computer Programming, Data Mining, Data Visualization, Python (Programming Language), Machine Learning, Monte Carlo Methods, Software Engineering, Information Technology, Machine Learning Operations, Markov
- **Published:** August 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1f6745abb81776af

## About the Role

* BS and/or MS degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field
 * Excellent communication skills
 * Programming experience with Python
 * Proficient knowledge of machine learning and data mining algorithms
 * Expertise in Finite Element Analysis (Strand7, RAM, SAP200, etc.) a plus

## Description

Thornton Tomasetti is seeking a Civil/Structural Engineer with a Data Science background to contribute to CORE.AI, a dedicated research and development team focusing on Artificial Intelligence and Machine Learning (AI/ML) projects. You'll be a key part of the team supporting the Director CORE.AI and CORE, the software development, R&D, and advanced computational modeling studio at Thornton Tomasetti.

The goal of the role will be to drive AI/ML tools and processes that will provide both insight and production value to Thornton Tomasetti practices and technical staff. You'll need to be highly motivated and have demonstrated experience in analyzing and creating data sets to enable AI/ML model creation that can be utilized in production applications. You will work in a collaborative environment as you support, build, and maintain applications for the broader staff.

What You'll Do

 * Use statistical inference (Bayesian and Markov Chain Monte Carlo methods) for probabilistic design space exploration.
 * Prepare data visualizations to illustrate and explain analytical results.
 * Use finite element analysis, and other numerical methods to analyze and design code-compliant structural components and systems for data set preparation.
 * Use constrained multi-objective optimization, and other computational methods for design space exploration and sensitivity analysis.
 * Utilize techniques like regression, clustering, and optimization


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