Data Engineer – AI & Machine Learning

Integral Federal is hiring a Data Engineer – AI & Machine Learning to support its internal Office of Technology and build capabilities for AI and machine learning initiatives. The role designs data architectures and pipelines, integrates and tunes AI models, engages government stakeholders, and ensures solutions meet federal security and governance standards.

Responsibilities

• 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)

Preferred

• Currently holding an active DoD Secret, Top Secret, or TS/SCI clearance is desirable
• Prior experience consulting or working directly with the DoW, Intelligence Community, or DHS
• DoW experience
• Intelligence Community experience
• DHS experience

Benefits

• Hybrid schedule with 3 days in the office
• Eligible for overtime, shift differential, and/or discretionary bonuses, depending on the position
• Paid parental leave
• Immediate vesting in the 401(k)
• Medical, Dental & Vision Insurance
• Flexible Spending Accounts
• Short-Term and Long-Term Disability Insurance
• Life Insurance
• Paid Time Off & Holidays
• Earned Bonuses & Awards
• Professional Training Reimbursement
• Employee Assistance Program

Company

• Integrated digital transformation and systems engineering for national security
• Mclean, Virginia, USA
• http://www.integralfed.com/
• Founded in 1985
• 201-500 employees

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related highly technical field
• 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
• 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)
• Must be eligible to obtain and maintain at least a **DoD Secret Clearance**
• Master's degree in Data Science, AI, or a related field
• Deep understanding of MLOps frameworks, containerization (Docker, Kubernetes), and CI/CD pipelines for machine learning
• Currently holding an active DoD Secret, Top Secret, or TS/SCI clearance is desirable
• Prior experience consulting or working directly with the DoW, Intelligence Community, or DHS
• 3+ years of progressive data engineering experience, with at least 2+ years specifically dedicated to supporting Artificial Intelligence and Machine Learning operations (MLOps).

Required skills

• AWS GovCloud, Amazon Redshift, Azure Government, CI/CD for Machine Learning, Databricks, Docker, ETL/ELT Pipeline Engineering, Hugging Face, Kubernetes, MLOps, Multimodal Data Engineering, Pandas, PySpark, PyTorch, Python, SQL, Snowflake, TensorFlow

Experience

• 3+ years