Agile Defense builds and operationalizes AI-enabled data solutions for mission-critical work with the Department of Defense. This onsite Data Scientist / Engineer role supports the CDAO ADA IR program, helping teams turn raw data into decision-support capabilities through scalable pipelines, machine learning services, and secure deployments in containerized environments.
How you’ll contribute
You’ll support the full lifecycle of AI-enabled data capabilities, from design and development through operational deployment. The work centers on building and evolving data pipelines, pre-processing workflows, feature engineering strategies, and machine learning services that can run reliably in secure, containerized environments.
- Support design, development, and operational deployment of scalable AI-enabled data solutions for the CDAO ADA IR program.
- Shape and deploy data pipelines, pre-processing workflows, feature engineering strategies, and ML services in secure, containerized environments.
- Collaborate with product managers, full-stack developers, platform engineers, and mission stakeholders to convert raw data into meaningful insights and decision-support tools.
- Work within multidisciplinary teams applying advanced analytics, machine learning, and engineering practices in mission-critical environments at Combatant Commands.
- Operate in agile environments focused on reproducibility, testing, and continuous delivery.
What you bring
- 4+ years of experience in applied data science, machine learning engineering, or data pipeline development.
- Proficiency in Python and SQL, plus distributed data frameworks such as Spark (including Databricks and PySpark).
- Background aligned with one of the following: a bachelor’s degree plus 3 years of recent specialized experience, or an associate’s degree plus 7 years of recent specialized experience, or a major certification plus 7 years of recent specialized experience, or 11 years of recent specialized experience.
Tools and focus areas
Experience with ML and deployment workflows is important for this position. Your work may include model development and productionization with scikit-learn, TensorFlow, XGBoost, and MLflow, along with MLOps practices. You’ll also use API development and secure cloud environments such as AWS, Azure, and Palantir Foundry.
- Develop ML models from training to deployment using standard libraries and tooling (for example: scikit-learn, TensorFlow, XGBoost, MLflow).
- Apply knowledge of MLOps, API development, and secure cloud-based environments (AWS, Azure, Palantir Foundry).
- Demonstrate data validation, model testing, and performance evaluation.
- Use visualization and storytelling tools such as Tableau, Plotly, or Matplotlib.
- Communicate technical concepts effectively to non-technical audiences.
Working conditions and clearance
- Onsite work in a SCIF is required.
- Top Secret clearance with the ability to obtain SCI; Must Have Clearance to Start.
Location
In Person: Falls Church, VA (also listed: Ft. Meade, MD, Stuttgart, Baden-WĂĽrttemberg, Germany, Tampa, FL, Honolulu (Camp H.M. Smith), HI, Colorado Springs, CO, Doral (Miami area), FL, Omaha (Offutt Air Force Base), NE, Scott Air Force Base, IL).
Core values
- Happy - Be Infectious: create a positive, connected environment.
- Helpful - Be Supportive: teamwork built on support and collaboration.
- Honest - Be Trustworthy: transparent communication and ethical conduct.
- Humble - Be Grounded: mutual respect and a willingness to learn.
- Hungry - Be Eager: drive for excellence and continuous improvement.
- Hustle - Be Driven: go above and beyond to advance the mission.
