Lumotive is pioneering the era of programmable optics—where light is controlled as intelligently and flexibly as software.
At the heart of this transformation is a once-in-a-generation innovation: a flat CMOS-based “general purpose optic.” Lumotive’s Light Control Metasurface (LCM™) beam forming chips can be programmed to function as a beam steering mirror, a lens, mirror, a beam splitter—or any optical function—replacing bulky and mechanical optical components with a fully digital, reconfigurable semiconductor . This breakthrough lays the foundation for a massive shift in multiple technologies—from 3D sensing and imaging to optical networking, free space optical communication, and beyond. Like the shift from analog to digital in electronics, programmable optics will reshape industries from robotics, self-driving cars, AI, defense, and healthcare.
Lumotive’s first commercial application is in LiDAR, where its software-defined beam steering chips are already enabling compact, high-performance, solid-state sensors. These sensors are being deployed today in smart infrastructure, robotics, and mobility systems through leading module makers and solution integrators.
With more than 200 patents and growing commercial traction, Lumotive is delivering the world’s first digital platform for light—and redefining what’s possible in the optical age.
Job Description:
The Optical Systems Engineer plays a key role in a start-up environment developing the next generation of LiDAR. This hands-on role blends developing knowledge of optics, electronics, and software – expect to build, test, debug, and refine real hardware in the lab. You'll work within established architecture, technical direction, and defined procedures, exercising good judgment to determine appropriate action on problems of moderate scope, and building productive working relationships across internal teams. You'll receive general instructions on routine work and detailed instructions on new projects or assignments. This position reports to the Senior Manager of Optical Systems Engineering.
Responsibilities:
Support the implementation of LCM-based lidar system and transmitter designs within established architecture and technical direction, contributing to the build and test of our reference designs, including debug, customization, and system-level optimization, in collaboration with hardware, optics, firmware, and software teams.
Build test stations and fixtures for system-level test, assembly, and calibration, supporting bring-up through production, following established designs and procedures.
Execute system-level test campaigns to characterize and validate lidar performance across development and production builds.
Build and maintain Python-based automation and measurement tools for characterization and calibration of system and optoelectronic components (lasers, detectors).
Debug systems and transmitters — including electronics, optics, and embedded processing and control algorithms — to isolate and resolve performance and integration issues.
Participate in hardware and system design reviews, providing input on system integration, testability, and robustness for LCM-based lidar systems.
Report on system performance and test results, presenting data, methods, and conclusions clearly to the internal technical team.
Qualifications:
Bachelor's degree in Electrical Engineering, Optical Engineering, Physics, or related field plus a minimum of 2+ years of relevant work experience required.
Advanced degree preferred.
Working experience in optoelectronic or photonic systems integration and debug required.
Python skills for automation, control, and data analysis.
Familiarity with Git, Unix environments, and embedded systems.
Exposure to system integration, optoelectronics, and cross-domain debugging.
Exposure to designing or building test, assembly, or calibration stations, including fixture design and test automation.
Working familiarity with lasers, photodetectors, and optoelectronic component characterization.
Experience with lidar systems preferred; radar or ultrasound experience is also acceptable.
Ability to apply established calibration, optimization, and signal-processing approaches following defined procedures.
Good communication skills; comfortable building working relationships across teams.
