MEMS-based lidar sensors and perception software for automotive and industry
MicroVision builds lidar hardware and perception software for automotive, industrial, and security and defense customers. Its stack pairs FPGA, SystemVerilog, and DSP work with CUDA, TensorRT, and PyTorch, plus self-hosted OpenStack, Kubernetes, MLflow, and vLLM, which points to an on-prem ML platform for edge inference. Accelerating, senior- and staff-heavy engineering hiring alongside supply-chain pain points suggests a push from development toward manufacturing scale-up.
MicroVision is a public company headquartered in Redmond, Washington, founded in 1993, with 201–500 employees. It develops lidar sensors and a broader perception platform that combines hardware, software, and system-level engineering. Its roots are in MEMS laser beam scanning, precision optics, and embedded sensing, originally applied to micro-display systems. Target markets include automotive, industrial, and security and defense. Product work spans solid-state and FMCW lidar, 3D sensing, object detection, and 3D mapping, with functional safety standards such as ISO 26262 and IEC 61508 in scope.
MicroVision uses C++, Python, CUDA, TensorRT, PyTorch, and TensorFlow for perception and ML, FPGA design with SystemVerilog and Verilog, and infrastructure on OpenStack, Kubernetes, GitLab CI/CD, Jenkins, and AWS.
Yes. Hiring is accelerating, is mostly in engineering with some operations roles, and leans toward senior and staff-level positions. All open roles are based in the United States.
Current work includes automotive lidar product development, next-generation electro-optical sensors, an on-prem ML platform with LLM hosting, edge deployment for real-time lidar, and manufacturing scale-up.
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MicroVision®'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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