AI/ML Engineer
@ General Dynamics Information Technology

Hybrid
$82,000
Hybrid
Full Time
Posted 4 days ago

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Job Details

Overview

Join General Dynamics Information Technology as an AI/ML Engineer. Deliver insights to help clients turn data into action with innovative AI and machine learning solutions. You will work remotely utilizing analytical, statistical and programming skills to build models, analyze data, and develop transformative solutions.

Key Responsibilities

  • Collect, analyze, and interpret large data sets using Python.
  • Develop and implement machine learning models and simulations.
  • Analyze statistics, data and algorithms to recommend strategies.
  • Create data driven dashboards and prepare detailed reports.
  • Monitor, test, and document complex application programs.

What You’ll Need

A Bachelor’s degree or higher and 0+ years of experience in data analysis and AI development are required. Proficiency in Python, knowledge of ETL, data modeling, AWS, and familiarity with tools like Tableau and Salesforce are essential.

Work Environment & Benefits

This is a remote role offering a full flex work week, comprehensive benefits including 401K match, paid time off, and a positive culture focused on career growth and mission impact. You will join a global company known for digital modernization and advanced technology.

Key Skills/Competency

Machine Learning, Python, Data Analysis, AI, Data Engineering, ETL, AWS, Tableau, Simulation, Statistical Modeling

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How to Get Hired at General Dynamics Information Technology

🎯 Tips for Getting Hired

  • Research GDIT's culture: Review their mission, values, and employee reviews.
  • Customize your resume: Highlight AI, ML, and Python skills.
  • Practice technical challenges: Prepare for data and model discussions.
  • Prepare for behavioral questions: Reflect real-world problem solving scenarios.

📝 Interview Preparation Advice

Technical Preparation

Brush up on Python programming.
Review model simulation techniques.
Study data pipeline and ETL processes.
Practice machine learning algorithms.

Behavioral Questions

Describe managing remote project deadlines.
Explain conflict resolution in remote teamwork.
Discuss prioritizing tasks under pressure.
Share an example of effective collaboration.

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