Infrared sensors, compound semiconductors, and contract R&D for defense and space
Teledyne Scientific & Imaging pairs a government-funded research lab with an infrared imaging sensor business, and its stack shows both sides: CUDA, Python and FPGA/Verilog work for algorithms and hardware, plus Deltek Costpoint for government contract accounting. Hiring skews toward mid-level engineering and manufacturing while velocity is slowing, and recurring pain points center on wafer yield, throughput and process variation in HgCdTe detector production.
Teledyne Scientific & Imaging combines Teledyne Scientific Company, the parent group's central research laboratory, with Teledyne Imaging Sensors, which includes Teledyne Judson Technologies. The research arm takes technologies developed under U.S. Government R&D contracts and moves them into other Teledyne businesses, covering compound semiconductor devices, integrated circuits, ceramic and functional materials, real-time processing algorithms, and optical sensors. The imaging arm supplies infrared and visible sensors, read-out integrated circuits, scientific and tactical IR cameras, and laser protection filters for military, space, astronomy and commercial customers. The company is headquartered in Thousand Oaks, California, employs 201–500 people, and operates as part of a public company.
Its stack includes Python, C++, CUDA, MATLAB, Docker and CMake for software, FPGA, ASIC, Verilog and SystemVerilog for hardware, ANSYS Fluent and AutoCAD for engineering, and Deltek Costpoint, OneStream, TM1, Workday and Power BI for business systems.
Job posts point to infrared sensor and space technology programs, MBE growth of HgCdTe wafers for IR detectors, target detection and tracking, deep learning, brain-computer interfaces, and astronomy and earth observation programs.
The company is headquartered in Thousand Oaks, California, and its current hiring is focused in the United States, mainly in engineering and manufacturing roles.
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Teledyne Scientific & Imaging'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 →
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