AI/ML Engineer (Tactical Networks - CANES) | Active Secret clearance

General Dynamics Information Technology

102d • $108,979 - $147,443

About The Position

Transform data into decisive advantage as a AI/ML Engineer with GDIT. A career in applied machine learning at GDIT means building mission-grade analytics and automation that harden and optimize Navy tactical networks. You’ll be at the forefront of innovation—advancing Consolidated Afloat Networks and Enterprise Services (CANES) and related platforms with NIWC Pacific (Codes 55131/55132/55133) in support of PMW-160 Tactical Networks. At GDIT, people are our differentiator. Our work depends on a Senior AI/ML Engineer who can design, deploy, and sustain models at the edge—within virtualized, bandwidth-constrained, and intermittently connected environments—while meeting rigorous cybersecurity and programmatic standards.

Requirements

• Active Secret clearance.
• 2+ years applying AI/ML to large-scale or mission systems (time-series/graph/NLP), including production deployments and lifecycle sustainment.
• 2+ years MLOps (containerization, orchestration, CI/CD, model/version management, monitoring) and secure software practices.
• Hands-on data engineering with SQL/NoSQL, stream processing (e.g., Kafka), and Python-based ML stacks (PyTorch or TensorFlow, scikit-learn, pandas).
• Demonstrated delivery in constrained/edge environments (performance tuning, model compression/quantization, resilience to disconnection).
• Familiarity with DoD cybersecurity processes (RMF, STIGs) and documentation practices.
• BS in Computer Science, Electrical/Computer Engineering, Data Science, Applied Mathematics, or related field (equivalent experience may substitute per GDIT policy).

Nice To Haves

• Prior support to PMW-160/NIWC Pacific or CANES-like programs; understanding of Navy network operations, GPON, QoS, and transport/optical basics.
• Certifications: Security+ CE (or higher 8140 baseline if privileged access assigned), CKA/CKAD, AWS/Azure/GCP ML Specialty, Splunk Core/Enterprise.
• Experience with graph ML (PyG/NetworkX), time-series platforms (Kats, Prophet), and XAI (SHAP/LIME).
• Integration with observability stacks (Prometheus/Grafana), IaC (Ansible/Terraform), and secure SBOM/supply-chain controls.
• Participation in CCRI prep, DT/OT data analysis, and performance test harness development.

Responsibilities

• Design and implement ML solutions for network assurance and cyber defense: anomaly detection, fault prediction, QoS optimization, capacity planning, and automated triage across ashore/afloat/subsurface/airborne domains.
• Build secure data pipelines (ETL/ELT) from CANES telemetry, logs, and performance counters; develop features for time-series, graph, and NLP use cases; enforce data governance and labeling quality.
• Operationalize models with MLOps: containerize (Docker), orchestrate (Kubernetes/Openshift), version (MLflow/DVC), and automate CI/CD (GitLab/Jenkins) for model build/test/deploy in disconnected and low-bandwidth scenarios.
• Optimize for edge inference using ONNX/TensorRT and CPU/GPU acceleration; implement drift monitoring, retraining triggers, A/B or canary deployments, and model explainability for operator trust.
• Integrate analytics with enterprise tooling (e.g., REST/gRPC services, message buses, dashboards such as Grafana/Splunk) and with program configuration management (CMPro) and issue workflows (Jira/Confluence).
• Align solutions to Risk Management Framework (RMF) and DISA STIGs; produce artifacts (e.g., security design, data flows, test plans) supporting IATT/ATO packages in Enterprise Mission Assurance Support Service (eMASS) in coordination with IA teams.
• Support Developmental Test & Evaluation (DT&E), Test Readiness Reviews (TRRs), and lab events in NIWC Pacific facilities; collect test data, analyze results, and author technical reports/white papers.
• Mentor engineers and analysts on ML best practices; contribute to Systems Engineering Plans (SEPs) and DoD Architecture Framework (DoDAF) views related to data/analytics services.

Benefits

• Comprehensive benefits and wellness packages.
• 401K with company match.
• Competitive pay and paid time off.
• Full-flex work week to own your priorities at work and at home.
• 15 days of paid leave per calendar year.
• 10 paid holidays per year.
• Paid Family Leave program providing up to 160 hours of paid leave in a rolling 12 month period.
• Short and long-term disability benefits.
• Life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees