Computer Vision Analyst (Level II) - Top Secret clearance

Lockheed Martin•Littleton, CO

2d•Onsite

About The Position

We are seeking a motivated engineer to develop and support the end to end digital simulation platform. The ideal candidate will: Operate and update the simulation Conduct statistical analysis & uncertainty quantification via Monte‑Carlo simulations, Design‑of‑Experiments (DoE), sensitivity testing, and algorithm‑level error modeling Develop interactive dashboards, generate plots/reports for stakeholders, and tailor visual output for different audiences Define test cases, compare simulation results against analytical/ground‑truth data, document V&V evidence, and support formal review packages Debug computer‑vision algorithm performance in the simulation by debugging the underlying code and using visualizations to diagnose issues Collaborate with embedded‑hardware, optics, and systems teams to ensure the simulation reflects actual hardware behavior and integrates smoothly with downstream toolchains Generally has 1+ years of related experience and may have a post-secondary degree or training in a related discipline.

Requirements

Proficiency in Python (including libraries such as NumPy, SciPy, Pandas, and Bokeh)
Understanding of Statistical Methods (Monte‑Carlo, basic uncertainty quantification)
Ability to generate clear visualizations and communicate results to both technical and non‑technical audiences
Experience with Linux development environments and shell scripting
Proficiency in C++, including the ability to read, maintain, and/or extend C++ codebase
To meet requirements of the program/customer, this position requires the selected employee to be a U.S. Citizen.
Active Top Secret security clearance is necessary for consideration and is required prior to start.

Nice To Haves

Bachelor’s degree in Computer Science, Aerospace Engineering, Mathematics, or a related technical field (or equivalent professional experience) with 1+ year(s) of relevant experience
Experience with MATLAB
Foundational knowledge of core algorithms used in computer‑vision and signal‑processing (e.g., feature extraction, optical flow, SLAM, matrix factorization, optimization, linear‑algebra routines)
Docker - experience containerizing applications for reproducible builds and testing
CI/CD pipelines - familiarity with GitLab CI or similar tools for automated testing and deployment
Requirements verification

Responsibilities

Operate and update the simulation
Conduct statistical analysis & uncertainty quantification via Monte‑Carlo simulations, Design‑of‑Experiments (DoE), sensitivity testing, and algorithm‑level error modeling
Develop interactive dashboards, generate plots/reports for stakeholders, and tailor visual output for different audiences
Define test cases, compare simulation results against analytical/ground‑truth data, document V&V evidence, and support formal review packages
Debug computer‑vision algorithm performance in the simulation by debugging the underlying code and using visualizations to diagnose issues
Collaborate with embedded‑hardware, optics, and systems teams to ensure the simulation reflects actual hardware behavior and integrates smoothly with downstream toolchains