Principal Machine Learning (ML) Engineer

Experience building agentic workflows with tool calling, Model Context Protocol (MCP) implementations, and multi-step reasoning systems Deep understanding of transformer architectures and common frameworks like vLLM, Pytorch, Tensorflow Experience deploying ML services in secure environments with constrained resources Highly Preferred: Experience with edge AI and autonomous data fusion systems Highly Preferred: Familiarity with defense and national security applications Highly Preferred: Experience with browser-based geospatial visualization libraries (e.g., Leaflet, OpenLayers, Mapbox)

Help design, plan, implement, and guide enterprise AI/ML strategies. Extract valuable insights from customer data and operationalize AI at scale. Oversee all aspects of the ML lifecycle, including data collection, cleaning, pre-processing, model training, and production deployment. Build trustworthy, mission-critical AI systems. Work independently with customers to assist in developing new business opportunities. Introduce new technology into organizations to drive value from data using AI/ML. Build agentic workflows with tool calling, Model Context Protocol (MCP) implementations, and multi-step reasoning systems. Design, develop, and research Machine Learning systems, models, and schemes. Study, transform, and convert data science prototypes into production-ready systems. Search and select appropriate data sets before performing data collection and data modeling. Perform statistical analysis and use results to improve models. Train and retrain ML systems and models as needed. Identify differences in data distribution that could affect model performance in real-world situations. Visualize data for deeper insights. Analyze use cases of ML algorithms and rank them by success probability. Understand when findings can be applied to business decisions. Enrich existing ML frameworks and libraries. Deploy ML services in secure environments with constrained resources. Verify data quality and ensure it via data cleaning.