Senior Embedded Research Software Engineer

Intuitive•Sunnyvale, CA

7h•$185,000 - $266,200•Onsite

About The Position

As a Senior Embedded Research Software Engineer in the Future Forward organization, you will be at the forefront of innovation, rapid prototyping, and new product development. You will collaborate with talented cross-functional teams—including engineers, clinicians, and product managers—to advance Intuitive’s robotic surgical platform, driving the product lifecycle from concept to launch. In this role, you will design, develop, and integrate embedded and platform software across a complex robotic system. This includes interfacing with hardware, firmware, control algorithms, vision pipelines, user interfaces, and test infrastructure such as fault-injection and diagnostic frameworks. You will contribute to the architecture, implementation, and system-level integration of advanced functionalities into complete surgical robotic platforms, supporting early-stage product exploration and development. Success in this role requires excelling in an agile, small-team environment—transforming initial concepts into robust prototypes, iterating methodically, and consistently maintaining exceptional product quality with a patient-first mindset.

Requirements

Master’s degree or higher in Computer Science, Computer Engineering, or a similar technical field. Advanced degrees are preferred.
Minimum of 8 years (or 6 years with a Master’s degree, or 3 years with a Ph.D.) of experience developing embedded systems software, including at least 2 years in an R&D, innovation, or exploratory environment.
Proficiency in multiple programming languages (e.g., C, C++, Python, Matlab).
Experience with multi-threaded and multi-processor/multi-core systems.
Proven track record in building real-time applications and/or embedded software.
Demonstrated experience with industrial embedded operating systems (e.g., QNX, Yocto), hardware interfaces, FPGA, CUDA programming, and the latest technology stacks for embedded software development.
Proficiency in profiling and debugging system software to optimize performance.
Strong problem-solving skills, with the ability to structure and iterate on solutions in ambiguous contexts.
Excellent written and verbal communication skills.

Nice To Haves

Expertise in building AI/ML-based embedded solutions using the latest tech stack, frameworks, and tools to achieve the desired performance through hardware acceleration and other techniques.
Hands-on experience integrating the latest AI/ML models to develop embodied AI applications.
Proven experience applying software innovation within healthcare, robotics, or other complex technology sectors.
Track record of contributions to research publications, patents, or open-source projects.
Demonstrated ability to swiftly adapt to new technologies and domains, using curiosity and creativity to solve problems.
Proven capability to apply systems thinking in the design and evaluation of complex solutions.

Responsibilities

Collaborate cross-functionally during early-stage product exploration, prototyping, and development to address clinical, functional, performance, and safety requirements with key stakeholders.
Translate early requirements into prototype implementations to evaluate, iterate, and advance novel robotic systems.
Design and develop robust embedded software to enable system infrastructure, including OS drivers, hardware interfaces, real-time data pipelines, inter-processor communication, error handling, and user/test applications.
Act as a subject matter expert in embedded software development by developing prototypes from early requirements, rapidly iterating, and creating a functional product for research studies, employing systems thinking to integrate technology, users, and workflows.
Refine and iterate designs, balancing technical requirements, feasibility, schedules, and resource constraints.
Apply strong software engineering practices, including writing maintainable code, modular architecture, testing, and documentation.
Adapt to project needs by initially exploring a broad range of software technology stacks and delving deeper into specific areas as the project evolves.
Identify, document, and communicate intellectual property generated during development.