Senior Systems GPU Engineer – AI & Robotics

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here. Primary Function of PositionAs a Senior Systems GPU Engineer – AI & Robotics, you will be responsible for iteratively improving and integrating high performance robotic AI with MLE product teams.You will work alongside research, SW/ HW/ ML engineering, regulatory, controls and clinical teams to translated early pre-product ML algorithms into performance optimized, robust, validated and scalable medical device products and infrastructures, including edge and cloud.Responsibilities• GPU & Model Performance & Optimization: Advanced skills using performance profiling, tracing, and debugging tools (e.g. NVIDIA Nsight Systems, Nsight Compute, to identify code or hardware bottlenecks and implement improvements• System Architecture & Integration: Design and optimize software interfaces between robotic subsystems, ensuring seamless integration between edge AI, firmware, OS, hardware, and cloud services. You will oversee the deployment and continuous improvement of these systems to ensure high reliability and performance.• Linux Systems & Virtualization: Development of Linux kernel internals, device drivers, memory management, and containerized GPU runtime environments (e.g., Docker, NVIDIA Container Toolkit, Kubernetes)• Project Ownership & Strategy: Lead complex, end-to-end embodied intelligence projects, making critical architectural decisions and technical trade-offs. You will define the strategic roadmap for the robotics platform—from foundational models to real-time onboard inference—while serving as a core contributor to team planning and design reviews.• Cross-Functional Collaboration: Partner with motion controls, perception, and hardware teams during early-stage exploration to address clinical, functional, and safety requirements. You will work closely with the research and product development teams to integrate perception, planning, navigation, and multimodal ML models onto edge platforms.• Iterative Development: Refine designs by balancing technical feasibility with sch...