Senior Software Engineer — VETi Platform
Palo Alto, CAFull-time$140–220K/yrPosted 4mo agoStill listed 3 days ago
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Job overview
Kodiak Sciences is hiring a Senior Software Engineer — VETi Platform. Kodiak Sciences seeks a Senior Software Engineer to build the software foundation for its AI‑enabled VETi wearable platform, spanning early prototypes to reliable engineering systems, collaborating across hardware, optics, algorithms, and machine learning teams.
Key focus areas include Own the design, development, and optimization of software for advanced wearable imaging and sensing systems, Build software for device control, imaging workflows, AR/VR interfaces, and health‑monitoring applications, and Develop and integrate real‑time signal‑processing and image‑processing pipelines.
Successful candidates bring B.S. In Computer Science, Electrical Engineering, Computer Engineering, Or Related Technical Discipline Or Equivalent Practical Experience and 5+ Years Professional Software Engineering Experience Developing Complex Systems. Important skills include C, C++, Python, Software Architecture, Debugging, and Problem Solving. Preferred (not required): Embedded Systems, Device Software, Hardware/Software Integration, and Medical Devices.
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Full job description
Kodiak Sciences (Nasdaq: KOD) is advancing vision science by integrating retinal biology, optics, artificial intelligence, medical imaging, and next-generation wearable technologies.
Our VETi™ — Visual Engagement Technology and Imager — platform is an AI-enabled wearable system combining advanced LiDAR, Optical Coherence Tomography (OCT), embedded computing, machine learning, and AR/VR technologies. VETi is being developed for applications in retina care, digital health, identity security, cognitive science, and broader AI-enabled vision technologies.
We are looking for a Senior Software Engineer to help build the software foundation for Kodiak’s VETi platform, from early prototypes through reliable engineering systems. This role is well suited for an engineer with strong software fundamentals who enjoys complex technical problems, works well across disciplines, and is excited to build software that connects closely with real-world hardware.
We are interested in strong software engineers who are curious about hardware and motivated to work on advanced medical imaging and wearable technologies.
Responsibilities Own the design, development, and optimization of software for advanced wearable imaging and sensing systems — from prototype through validation. Build software for device control, imaging workflows, AR/VR interfaces, and health-monitoring applications. Develop and integrate real-time signal-processing and image-processing pipelines. Work with embedded computing platforms, sensors (LiDAR, OCT, MEMS-based systems), and hardware-accelerated processing (NPUs and similar). Collaborate with hardware, firmware, optics, algorithms, machine learning, and systems engineering teams. Develop and debug software at the application, hardware/software integration, and system levels on Linux and Windows. Take research prototypes and turn them into reliable engineering software that powers next-generation medical imaging devices used in clinical and product validation. Education / Qualifications
B.S., M.S., or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or a related technical discipline, or equivalent practical experience. 5+ years of professional software engineering experience developing complex systems. Strong programming experience in C, C++, and Python. Strong software architecture, debugging, and problem-solving skills. Experience building software that interfaces with hardware, sensors, devices, imaging systems, or performance-sensitive systems. Experience working in Linux and/or Windows environments. Ability to collaborate across software, hardware, scientific, and engineering teams. Additional Experience That Would Be Valuable
Experience with embedded systems, firmware, device software, or hardware/software integration. Experience developing medical devices, imaging systems, AR/VR systems, robotics, or wearable technologies. Experience with real-time signal processing, image processing, FFT pipelines, sensor data, or performance optimization. Experience with GPUs, DSPs, NPUs, FPGAs, microcontrollers, or other hardware-accelerated computing platforms. Deep learning experience, particularly in computer vision; experience integrating machine learning models into edge devices.
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