Modernizing the F-35 Integrated Test Force
Year
2025-2026
I worked as an Aeronautical Engineer at Lockheed Martin with the F-35 Program. To ensure smooth data collection, software configuration changes, structural maintenance, and troubleshooting, I adjusted an extensive dataset of protocols specific to the aircraft that influence how customers and the military fleet function in real-time.
Leveraging my knowledge of machine learning and artificial intelligence, I integrated Lockheed Martin proprietary technology to increase our test force efficiency. I developed a showcase of secure, agentic RAG for a breadth of confidential standard operating procedures (SOPs), contact lists, approved guidelines, software information, and basic aircraft documentation for project managers. This LLM agent (based on Llama Scout) has since, greatly increased the efficacy of seasoned and new recruits by providing references and direction for a given problem.
With awareness of advanced DoD-partnered innovation, I brought in new technology for the F-35 program to make use of our unique testing environment. Leadership behind automation programs, pilot training, and AI are some of the branches I was coordinating with to help Lockheed Martin labs assess performance, improvement points, and acquire real-use data.
Disciplines
Artificial Intelligence
Physics
Product Design
Manufacturing
Procurement
Data Analysis
Deploying Guidance, Navigation, and Controls for Reentry Vehicles
Year
2026
I transitioned from the F-35 Integrated Test Force into Lockheed Martin’s Space program as a Guidance, Navigation, and Control Engineer. In this role, I develop and validate GNC algorithms for reentry vehicles and counter systems, working across the full simulation stack. Day to day, this involves integrating Matlab/Simulink models into high-fidelity 6-DOF C++ simulations, building and testing new source code across C++, Python, and Linux environments, and executing software on high-performance computing clusters.
I collaborate closely with performance analysts and flight software teams in an Agile DevOps environment, using containerized infrastructure (Docker, Kubernetes) to support rapid iteration. My work sits directly at the intersection of control theory, algorithm development, and systems-level engineering.
Disciplines
Machine Learning
Physics
Simulation
GPU HPC
Agile DevOps
Flight Software
Algorithm Development