Lead AI/ML Engineer for Intelligence & Mission Systems

CACI International Inc.; Maryland; On-site; USD 126,000 - 277,000; Full time

Job summary

CACI International Inc. is seeking an AI/ML Engineer Lead to drive advanced AI/ML solutions for DoD intelligence, electronic warfare, and cyber systems. You will architect pipelines, lead data science initiatives, and mentor teams to deliver automated analytics and decision support.

Responsibilities include deploying ML models, NLP, CV, and MLOps practices, while interfacing with engineers and government stakeholders to ensure secure, scalable implementations.

Qualifications

• Active security clearance required (Secret to start, TS/SCI desired).
• Minimum 10+ years of professional data science/AI/ML engineering experience.
• Proficiency in Python, R, or similar.
• Proven ability to deploy ML models in production environments.
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras).
• Strong statistical, probabilistic, and mathematical modeling skills.

Responsibilities

• Design and develop ML models using supervised and unsupervised techniques.
• Implement NLP, computer vision, and deep learning solutions.
• Develop and maintain AI/ML data pipelines and MLOps workflows.
• Architect AI/ML pipelines for intelligence exploitation and automation.
• Lead technical teams and mentor junior data scientists.

Skills

Python

R

TensorFlow

PyTorch

Scikit-learn

Keras

Pandas

NumPy

SQL

NoSQL

NLP

CV

ML Ops

Communication

Leadership

Education

Master's degree in Computer Science/Data Science/Math/Statistics/Engineering

PhD (Desired) in Data Science/CS/Math/Statistics

Tools

TensorFlow

PyTorch

Scikit-learn

Keras

MLflow

Kubeflow

Job description

CACI International Inc. is seeking an AI/ML Engineer Lead to drive advanced AI/ML solutions for DoD intelligence, electronic warfare, and cyber systems. You will architect pipelines, lead data science initiatives, and mentor teams to deliver automated analytics and decision support.

Responsibilities include deploying ML models, NLP, CV, and MLOps practices, while interfacing with engineers and government stakeholders to ensure secure, scalable implementations.