Design and deploy machine learning, NLP, and collaborative analytics applications for Joint Staff national security missions. This role blends modern software engineering with applied data science in highly dynamic, classified environments requiring self-direction and rapid adaptation.
What you'll do
- Develop and deploy Python-based NLP and machine learning workflows including text analytics, topic modeling, embeddings-based classification, and entity extraction
- Build network analysis and knowledge graph systems using GraphRAG-like architectures for multi-source analytical problems
- Design and implement collaborative TypeScript front-end applications supporting real-time multi-user analytics, planning, and decision environments
- Build APIs, integrate data feeds, and support end-to-end data application pipelines within secure classified computing environments
- Evaluate emerging tools and methods to rapidly adapt customer capabilities for evolving Joint Staff mission requirements
- Provide technical documentation and iterative solution development in partnership with customer personnel and operational end-users
- Uphold security protocols and access policies while developing within SIPRNet and JWICS classified networks
Mission
Supporting Joint Staff strategic priorities through advanced analytics capabilities. Engineers operate within SIPRNet and JWICS classified networks, transforming siloed intelligence and operational data into actionable insights for DoD decision-makers with minimal supervision in a fast-moving contractor environment.
Required skills
- Python development
- Natural language processing
- Machine learning workflows
- TypeScript front-end development
- API design and integration
- Git version control
- Data pipeline architecture
- Knowledge graph systems