Senior Software Engineer – Simulation & ML Platform
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 Software Engineer – Simulation & ML Platform, you will build software platforms supporting simulation-based data generation and machine-learning development for robotic motion AI. You will work closely with Simulation Data Scientists and ML teams responsible for simulation strategy, synthetic-data design, action-model development, sim-to-real evaluation, and machine-learning experimentation. The Senior Software Engineer will translate those research and data-science requirements into reliable, scalable, and extendible software systems.ResponsibilitiesBuild and maintain software infrastructure for robotic simulations & ML using NVIDIA Isaac Sim, Isaac Lab, MuJoCo or custom simulation environments.Architect scalable pipelines for generating synthetic and procedurally varied robotic interaction data including development of APIs, configuration systems, command-line tools, and SDKs for defining and launching simulation workloads.Build automated integration and validation pipelines for evolving simulation platforms, physics engines, and the NVIDIA AI ecosystem, enabling rapid adoption of new releases while maintaining compatibility, reproducibility, and stability across the robotics simulation software stack.Develop AI-assisted engineering workflows for automated code refactoring, maintainability analysis, architectural consistency, and CI/CD optimization, enabling readable, modular, and sustainable codebases while improving engineering productivity across large-scale software projects.Create reusable abstractions for robot configurations, tasks, sensors, scene assets, domain randomization, failure injection, data capture, episode termination, and evaluation.Build tools that allow data scientists to define experiments without modifying low-level platform code. Support headless, interactive, local, cluster, and cloud-based execution.Develop secure, GPU-enabled containerized environments for simulation, data processing, model inference, and experimentatio...