ML Engineer: Cyber Threat Detection & Scalable AI

CACI

United States

On-site

USD 94,000 - 197,000

Full time

14 days+

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Job summary

CAC I is seeking an experienced Machine Learning Engineer to develop and deploy AI/ML systems defending the DoD AFI N. The role focuses on anomaly detection and threat intelligence, handling 1TB+ logs daily, and delivering defensible intelligence with measurable mission impact.

You will lead model design, data prep, evaluation, monitoring, and deployment while mentoring junior engineers and ensuring explainability.

Qualifications

Active TS/SCI clearance is required.
DOD Directive 8140.01 Security+ or equivalent within 6 months of hire.
5+ years in ML focused on production deployments.
Master's in Data Science, AI, or related field preferred.
Deep knowledge of ML frameworks such as PyTorch or TensorFlow.
Strong Python and ML library experience (Spark MLlib, Scikit‑learn, XGBoost, Keras, Hugging Face, PyTorch Geometric, MLflow).
Explainability tools like SHAP, GNNExplainer, or attention-based methods.
Experience with data from multiple sources, labeling, and pattern discovery.
Proficiency in visualization tools (Matplotlib, Grafana, Kibana).
Ability to communicate complex problems to non-technical leadership.

Responsibilities

Design, build, and deploy high-performance ML models with 1TB+ daily ingestion.
Lead data prep, model development, evaluation, monitoring, and retraining.
Develop state-of-the-art algorithms, including hybrid GNN/BiLSTM on dynamic graphs.
Improve model performance via feature engineering and hyperparameter tuning.
Mentor junior developers and provide technical guidance.
Document analytics and build product explainability into solutions.
Navigate constraints like data sharing limits, upstream failures, and data latency.