Data Engineer – AI & Machine Learning

Integral Federal•Tysons Corner, VA

1d•Hybrid

About The Position

Integral Federal is seeking a Data Engineer specializing in AI and Machine Learning to join its internal Office of Technology. The position focuses primarily on internal projects, building technical capabilities and best practices, with occasional support for billable client engagements. The engineer will serve as the data architectural backbone of AI and ML initiatives, designing data architectures and complex pipelines for structured, unstructured, and multimodal data. The role is based at Integral Federal’s headquarters in McLean, Virginia, with a hybrid schedule requiring three days in the office. Candidates must be able to obtain and maintain a DoD Secret Clearance; an active Secret clearance or higher is preferred. The role includes designing scalable data architectures for machine learning, analytics, and high-volume federal mission data; developing and maintaining ETL/ELT pipelines, including pipelines for synthetic data; and processing multimodal data such as text, imagery, sensor data, and audio/video. The engineer will evaluate and deploy AI models, including large language models, and optimize them for performance, accuracy, and scalability in secure environments. The position also involves engaging with Integral project personnel and federal stakeholders to gather requirements, translate mission needs into data solutions, and explain technical concepts to non-technical leaders. Data pipelines and ML architectures must comply with federal security, privacy, and governance standards, including NIST, FISMA, and the DoD Cloud Computing SRG.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related highly technical field.
At least 3 years of progressive data engineering experience, including at least 2 years specifically supporting AI 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 such as Pandas and PySpark.
Proven experience building complex ETL/ELT pipelines for unstructured and multimodal data.
Hands-on experience evaluating, fine-tuning, and deploying AI models, such as HuggingFace, PyTorch, or TensorFlow.
Experience with modern data warehousing and data lake architectures, such as Databricks, Snowflake, or Redshift.
Must be eligible to obtain and maintain at least a DoD Secret Clearance.

Nice To Haves

Active DoD Secret, Top Secret, or TS/SCI clearance.
Master’s degree in Data Science, AI, or a related field.
Prior experience consulting or working directly with the DoW, Intelligence Community, or DHS.
Deep understanding of MLOps frameworks, containerization with Docker and Kubernetes, and CI/CD pipelines for machine learning.

Responsibilities

Design, build, and optimize scalable data architectures supporting advanced ML models, analytics, and high-volume federal mission data processing.
Develop, construct, test, and maintain resilient ETL/ELT data pipelines, including pipelines for synthetic data.
Process and integrate structured, unstructured, and multimodal data, including text, imagery, sensor data, and audio/video.
Evaluate and deploy AI models, including large language models, and optimize them for performance, accuracy, and scalability in secure environments.
Engage with Integral project personnel and federal government stakeholders to gather requirements and translate mission needs into data solutions.
Present technical concepts to non-technical leaders.
Lead internal, non-billable capability development and flex onto billable client engagements as required.
Ensure data pipelines and ML architectures comply with federal security, privacy, and data governance standards, including NIST, FISMA, and DoD Cloud Computing SRG.