OKSI designs electro-optical and infrared sensor systems paired with embedded AI/ML for autonomous decision-making in defense, space, and maritime domains. The stack reveals a hardware-software hybrid: CAD/simulation tools (SolidWorks, ANSYS, NASTRAN) for sensor and airframe design alongside TensorFlow, PyTorch, and CUDA for real-time inference on edge hardware (Jetson, ARM). Active hiring is weighted toward engineering and operations roles, while projects span missile seeker assemblies and electric thrust-vector-control systems—indicating active production work alongside organizational scaling challenges in HR and multi-state compliance.
OKSI is a 51–200-person defense contractor headquartered in Torrance, California, specializing in custom electro-optical and infrared sensor systems integrated with AI/ML autonomy. The company serves warfighter, space, and subsea applications, with a 30+ year track record in sensor development and fielded systems. Their product portfolio includes hyperspectral and multispectral imaging, video-based navigation, image fusion, and autonomous targeting systems. Current operations span sensor design, mechanical and electrical engineering, manufacturing, and embedded autonomy—with ongoing projects in seeker assemblies, electric thrust-vector-control systems, and facility infrastructure.
OKSI uses TensorFlow, PyTorch, OpenCV, and CUDA for real-time AI inference, paired with Jetson and ARM edge hardware for autonomous vision processing in embedded systems.
OKSI's engineering stack includes SolidWorks, ANSYS, NASTRAN for structural analysis, Altium and KiCad for PCB design, and MATLAB for signal processing and algorithm development.
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OKSI'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.