Deca Defense is looking to support the development of internal AI tooling, model training pipelines, and distributed deployment systems to eliminate warfighter pain points by developing custom autonomous solutions that directly resolve critical field challenges.
Requirements
- Strong Python proficiency with experience in API design, data structures, and scripting.
- Basic knowledge of PyTorch or TensorFlow with interest in model design, training, and optimization.
- Familiarity or curiosity about Docker, Kubernetes, MLflow, or Airflow.
- Interest in learning how models are deployed, managed, and scaled across multiple edge devices.
- Comfortable with Git and collaborative workflows.
- Learn version control (Git), modular programming, and CI/CD fundamentals within a supervised engineering environment.
Responsibilities
- Learn how Python-based tools are used to support model training, experiment tracking, and dataset management.
- Observe and participate in supervised development of components for data ingestion, preprocessing, training, and deployment pipelines.
- Gain practical familiarity with PyTorch and TensorFlow, including training fundamentals and model evaluation.
- Learn how AI models can be deployed across multiple edge devices, with attention to efficiency and synchronization.
- Practice writing basic Python scripts and APIs for automating small portions of ML workflows.
- Learn to visualize and track model and system performance using logging tools and lightweight dashboards.
- Gain exposure to integrating systems with MLOps tools
Other
- Unpaid Internship (25 hours per week)
- In compliance with the International Traffic in Arms Regulations (ITAR), only U.S. citizens are eligible to apply.
- Pursuing or recently completed a degree in Computer Science, Software Engineering, or a related technical field.
- Work directly on projects that support AI autonomy in real defense applications.
- Collaborate with a team where practical engineering meets real-world mission experience.
