Advancing the Department of Defense's mission to keep our country safe and secure by transforming data into decisive advantage as an AI/ML Engineer with GDIT, building mission-grade analytics and automation that harden and optimize Navy tactical networks.
Requirements
- 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.
- 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.
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.
Other
- Secret Clearance
- US Citizenship Required
- ~10–25% CONUS/OCONUS travel to labs, shipyards, and fleet concentration areas per tasking.
- BS in Computer Science, Electrical/Computer Engineering, Data Science, Applied Mathematics, or related field (equivalent experience may substitute per GDIT policy).
- 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.
