Custom scientific software for imaging, visualization, and high-performance computing
Stellar Science builds domain-specific software for computational imaging, 3D visualization, and physics simulation—stacks C++, Python, and GPU compute (PyTorch, TensorFlow, OpenCV) alongside HPC tools (MPI, OpenMP). The tech shape (deep scientific libraries, OpenGL/WebGL rendering, and heavy numerical compute) mirrors their project portfolio: space domain awareness, directed energy simulation, and laser effects modeling. Engineering-heavy hiring (8 of 9 open roles) with a mix of mid and senior engineers signals scaling of complex solver and visualization work; two named pain points around government compliance and IT infrastructure suggest they're moving upmarket into defense/federal contracts.
Stellar Science develops custom software for research and engineering teams in scientific computing, computer vision, and 3D visualization. Founded in 1999 and based in Albuquerque, New Mexico, the company operates across domains including image enhancement, computational electromagnetics, scene simulation, and thermal modeling. Their software runs on systems ranging from desktop workstations to high-performance supercomputing clusters. Current project focus includes space situational awareness, directed energy simulation, and image generation—indicating work in defense, aerospace, and federal R&D sectors. The company is 51–200 employees and privately held.
C++, Python, and Java are their core languages. The stack also includes modern C++ standards (C++20, C++23), GPU frameworks (PyTorch, TensorFlow), and scientific libraries (OpenCV, NumPy, SciPy, scikit-learn).
Current projects include space situational awareness software, computer vision tools, directed energy simulation, space domain awareness systems, image simulation, and laser source generation and effects modeling.
Stellar Science Ltd Co's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.