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# nData Engineer for AI and Machine Learning

- **Company:** Integral Federal
- **Location:** McLean, VA, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, SQL Databases, Data Processing, Cloud Platform System, Pytorch, Snowflake, Pandas, Data Lakes, Pyspark, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, Data Pipelines, Docker, Amazon Redshift, Databricks
- **Published:** October 27, 2026
- **Apply:** https://jobs.military.com/career/375046/data-engineer-ai-machine-learning-virginia-va-tysons-corner

## About the Role

* Education: Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related highly technical field.\n
 * Experience: 3+ years of progressive data engineering experience, with at least 2+ years specifically dedicated to supporting Artificial Intelligence and Machine Learning operations (MLOps). Strong background working with and deploying in cloud environments, particularly AWS GovCloud or Azure Government.\n
 * Technical Skills:\n

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 * Expert-level proficiency in Python, SQL, and data manipulation libraries (Pandas, PySpark, etc.).\n
 * Proven experience building complex ETL/ELT pipelines for unstructured and multimodal data.\n
 * Hands-on experience evaluating, fine-tuning, and deploying AI models (e.g., HuggingFace, PyTorch, TensorFlow).\n
 * Experience with modern data warehousing and data lake architectures (e.g., Databricks, Snowflake, Redshift).\n, * Active Clearance: Currently holding an active DoD Secret, Top Secret, or TS/SCI clearance is desirable.\n
 * Advanced Degree: Master's degree in Data Science, AI, or a related field.\n
 * Federal Experience: Prior experience consulting or working directly with the DoW, Intelligence Community, or DHS.\n
 * MLOps Mastery: Deep understanding of MLOps frameworks, containerization (Docker, Kubernetes), and CI/CD pipelines for machine learning.\n