Sr. AI/ML Engineer, Cybersecurity (TS/SCI Eligible)

Skills

• ai
• analytics
• anomaly-detection
• aws
• azure
• cloud
• cybersecurity
• data-science
• databricks
• dns
• edr
• gcp
• generative-ai
• machine-learning
• mlops
• neural-networks
• nlp
• predictive-analytics
• prototyping
• python
• pytorch
• reinforcement-learning
• scikit-learn
• siem
• spark
• sql
• tensorflow
• threat-hunting
• threat-intelligence
• transformers
• typescript
• xdr

Must have

1. 5+ years of experience in artificial intelligence, machine learning, data science, cybersecurity analytics, or related technical disciplines.
2. Strong proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or comparable technologies.
3. Demonstrated ability to develop, train, evaluate, tune, and deploy machine-learning models for anomaly detection, behavioral analytics, threat identification, predictive analytics, or classification.
4. Applied knowledge of cybersecurity operations, threat hunting, threat intelligence, and identifying malicious or anomalous activity across enterprise environments.
5. Hands-on experience integrating large-scale cybersecurity datasets, including network traffic, DNS telemetry, endpoint activity, security logs, and threat intelligence, to support automated analytics,
6. Working knowledge of advanced AI/ML techniques, including neural networks, transformers, natural language processing (NLP), unsupervised learning, and generative AI.
7. Understanding of human-in-the-loop AI workflows, model explainability, and analyst validation, including the ability to evaluate AI/ML outputs, reduce false positives, and improve detection accuracy.
8. Ability to deploy, integrate, and sustain AI/ML capabilities within secure enterprise, cloud, or mission environments.
9. Ability to translate complex mission and technical requirements into scalable AI/ML solutions that support operational cyber teams.
10. Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Mathematics, or a related technical field.

Nice to have

1. Background supporting Intelligence Community (IC), DoD, Special Operations, JSOC, or other national security cyber missions.
2. Familiarity with MITRE ATT&CK, adversary tactics, techniques, and procedures (TTPs), attack-path analysis, and advanced persistent threat (APT) detection.
3. Experience with large-scale data processing and engineering technologies such as Spark, Databricks, SQL, graph databases, or distributed analytics platforms.
4. Knowledge of advanced machine-learning approaches, including autoencoders, reinforcement learning, synthetic data generation, and adaptive learning.
5. Familiarity with SIEM, EDR, XDR, threat intelligence platforms, or other cybersecurity monitoring and detection technologies.
6. Experience with cloud-based AI/ML development using AWS, Azure, or Google Cloud Platform, including containerized deployments.
7. Understanding of MLOps practices, including model lifecycle management, drift detection, automated retraining, versioning, and continuous improvement.
8. Background in cyber-focused research and development, rapid prototyping, or transitioning emerging AI/ML technologies into operational capabilities.
9. Knowledge of responsible AI, model security, explainable AI (XAI), and governance requirements within classified or sensitive environments.
10. Relevant AI/ML, cybersecurity, data science, or cloud certifications.

Full description