Staff Software Engineer - Vision - New Platforms

Job description

Primary Function of Position

As a Vision Software Staff Engineer, you will act as the technical lead for the software and embedded architecture definition of the real-time, high-definition video processing, imaging, and intra-body illumination systems at the heart of a new generation surgical robotic platform. You will drive the deep integration of cameras, image sensors, and vision processing pipelines into complex, multi-processor embedded architectures, bringing sound engineering judgment to the trade-offs between hardware, software, and algorithms, and procedure-specific product requirements.

Critical to the success of this role is experience diagnosing and debugging complex vision systems end-to-end – from sensor and optics through the video pipeline to software – driving root cause investigations and collaborating with hardware and algorithms teams to resolve difficult, multi-disciplinary issues. Familiarity with working in a regulated industry and with design controls for medical devices is a plus. The successful candidate must excel at evaluating design trade-offs through detailed technical deep dives, proof-of-concept development, and rapid iteration, translating rough requirements into robust, well-reasoned embedded software architectures.

A strong sense of shared responsibility and shared reward is required, as is the ability to make the work fun and interesting. Supporting you will be a development and management team that knows and cares about what you are doing and wants you to succeed.

Essential Job Duties

Lead the definition of hardware, software, and algorithms architecture for the real-time video processing engine, image sensors, and intra-body illumination systems of a new generation surgical robotic platform, from concept through implementation. Drive the integration of cameras, image sensors, and vision processing pipelines into complex, multi-processor embedded architectures, ensuring robust interfaces between hardware, FPGA/ISP, and software components.

Evaluate multiple design trade-offs for the embedded vision software architecture through detailed technical deep dives, proof-of-concept development, and rapid iteration. Lead bring-up and integration of new, high-performance cameras and image sensors, and the integration and evaluation of advanced camera pipeline video processing algorithms. Diagnose and debug vision system issues end-to-end – sensor, optics, video pipeline, and software – leading root cause investigations in close collaboration with hardware, algorithms, and systems engineering teams.

Drive development and enhancement of the color and power control functions for intra-operative illumination. Lead formal risk analyses for vision and illumination subsystems; identify additional hardware requirements and develop software mitigations to minimize potential failures. Design and develop offline simulation environments and hardware/software diagnostic tools that accelerate development, debug, and test. Perform and guide detailed design, development, documentation, and verification of embedded vision software and supervisory state machines, in compliance with regulatory requirements and Intuitive's internal guidelines.

Contribute broadly across the video and vision software stack, including extension of current processing frameworks to new hardware platforms. Apply high-level and specialized imaging/vision expertise to deliver innovations and problem-solving approaches that can be leveraged across multiple products. Mentor and guide engineers across the vision team.

Qualifications

Required Education and Training Bachelor's degree or above in Computer Science, Electrical Engineering, Computer Engineering, or a similar technical field. A minimum of 12 years of experience developing and supporting embedded systems, with significant focus on video, imaging, or vision systems (or 8 years with a Master's degree, or 5 years with a PhD).

Required Skills and Experience

Fluent in designing and developing mission-critical, cross-platform code in C/C++ for embedded, real-time, Linux-based systems, including application-level and driver-level development for multi-core and multi-processor architectures. Deep familiarity with integrating cameras, image sensors, and vision processing pipelines into complex embedded architectures, including hardware, software, and algorithm interfaces. Demonstrated ability to debug and diagnose complex vision system issues through root cause investigation and close cross-functional collaboration with hardware and algorithms teams.

Demonstrated ability to evaluate design trade-offs for embedded software architectures through detailed technical deep dives, proof-of-concept development, and rapid iteration. Direct experience with imaging devices – e.g., cameras, light sensors, video/graphics hardware – including sensor and camera bring-up, configuration, and integration. Fluent with image-processing concepts, camera pipeline video processing algorithms, and video processing frameworks.

Working knowledge of Python or other scripting languages for diagnostics, automation, and test. Demonstrated experience and comfort with all phases of the product development lifecycle, including design, documentation, implementation, debug, verification, validation, and transfer to manufacturing.

Preferred Skills and Experience

Knowledge of image-processing, CUDA, ML, and/or FPGA integration (e.g., Vivado and other FPGA development tools). Familiarity with communication protocols such as TCP/IP, CAN, and serialization protocols. Experience designing software products in a regulated industry or for mission-critical applications; comfort with concepts of design input, design output, traceability, risk analysis, and mitigations. Leadership of medical technology projects from inception through field validation to launch; strong understanding of the medical product ecosystem.

Familiarity with rapid development and rapid prototyping tools. Demonstrated capacity to relate to and mentor all levels of employees. Working Conditions none