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# Data Engineer AI & Machine Learning

- **Company:** Integral Consulting Services
- **Location:** Tysons, VA, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Data Warehousing, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Software Engineering, SQL Databases, Data Processing, Cloud Platform System, Pytorch, Large Language Models, Snowflake, Pandas, Containerization, Data Lakes, Pyspark, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, Data Pipelines, Docker, Amazon Redshift, Databricks
- **Published:** October 22, 2026
- **Apply:** https://www.jofdav.com/jobs/60232209-data-engineer-ai-machine-learning

## About the Role

Clearance Requirement: Ability to obtain and maintain a DoD Secret Clearance (Active Secret or higher preferred, * Education: Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related highly technical field.

 * 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.
 * Technical Skills:

 * Expert-level proficiency in Python, SQL, and data manipulation libraries (Pandas, PySpark, etc.).
 * Proven experience building complex ETL/ELT pipelines for unstructured and multimodal data.
 * Hands-on experience evaluating, fine-tuning, and deploying AI models (e.g., HuggingFace, PyTorch, TensorFlow).
 * Experience with modern data warehousing and data lake architectures (e.g., Databricks, Snowflake, Redshift).

Security Clearance: Must be eligible to obtain and maintain at least a DoD Secret Clearance.

Preferred:

 * Active Clearance: Currently holding an active DoD Secret, Top Secret, or TS/SCI clearance is desirable.
 * Advanced Degree: Master's degree in Data Science, AI, or a related field.
 * Federal Experience: Prior experience consulting or working directly with the DoW, Intelligence Community, or DHS.
 * MLOps Mastery: Deep understanding of MLOps frameworks, containerization (Docker, Kubernetes), and CI/CD pipelines for machine learning.

## Description

We seek an innovative and highly skilled Data Engineer for AI and Machine Learning to join our core technical group. This position sits within our internal Office of Technology, driving internal projects, building cutting-edge capabilities, and establishing best practices. You will interface with government stakeholders and may flex onto billable client projects as needed.

In this role, you will be the data architectural backbone of our AI and ML initiatives. You will design data architectures from the ground up and build complex pipelines for structured and unstructured multimodal data., * Data Architecture & Strategy: Design, build, and optimize scalable data architectures capable of supporting advanced ML models, analytics, and high-volume data processing for federal mission sets.

 * Pipeline Engineering (ETL/ELT): Develop, construct, test, and maintain resilient data pipelines, including those for synthetic data. Process and integrate complex, high-velocity structured and unstructured multimodal data (text, imagery, sensor data, audio/video).
 * AI/ML Integration & Tuning: Evaluate and deploy AI models (including Large Language Models). Ensure models are optimized for performance, accuracy, and scalability in secure environments.
 * Stakeholder Engagement: Interface directly with Integral project personnel and federal government stakeholders to gather requirements, translate mission needs into data solutions, and present technical concepts to non-technical leaders.
 * Project Flexibility: Lead internal, non-billable capability development while maintaining the agility to deploy onto billable client engagements as required.
 * Security & Compliance: Ensure all data pipelines and ML architectures adhere to strict federal security, privacy, and data governance standards (e.g., NIST, FISMA, DoD Cloud Computing SRG).