Machine Learning Engineer

Responsibilities

• Design, implement, and optimize scalable Simulation and RL infrastructure for training surgical robots in simulated environments, leveraging distributed systems for parallel processing and high-throughput simulations
• Optimize performance across the simulation stack, including distributed systems, Inference, and rendering, to ensure optimal usage of hardware resources and fast, efficient simulations
• Sim-to-Real Validation: Support efforts to reduce the sim-to-real gap through domain randomization, noise modelling, and physics-based constraints.
• Synthetic Data Generation: Develop simulation workflows to produce synthetic datasets for AI model training and validation.
• Designing large-scale data pipelines from multimodal robot sensor streams (vision, depth, proprioception, action logs)
• Running structured experimentation across architectures, datasets, and training strategies for physical AI systems
• Contribute to end-to-end learning pipelines from data collection → training → evaluation → real-world deployment
• Work with AI/ML engineers to integrate simulation outputs into training pipelines, especially for physics-informed models.
• Deliver high-quality, production-ready code in a dynamic and fast-paced environment
• Contribute to building new clinical datasets and data pipelines.
• Participate in integration of new ML/CV algorithms into existing and future robotic platforms.
• Collaborate with users and clinical advisors to iterate prototype designs based on feedback and performance.
• Experience and Abilities
• Doctoral degree in computer science, electrical and computer engineering, or Master's degree with minimum (5) years industry experience developing robotics and machine learning applications.
• Strong background in ML infrastructure, including designing training pipelines, data orchestration, and deployment of RL models at scale
• Proficiency in GPU optimizations for either inference or rendering
• Proficiency in Python, with familairty in frameworks like PyTorch, TensorFlow, or RL libraries, and a proven ability to write clean, scalable, and efficient code
• Ability to research, implement, and adapt cutting-edge techniques from academic and industry sources into practical, production-ready solutions for scalable RL in simulation
• Strong hands-on experience with Python (proficiency), C/C++ (proficiency), shell scripting
• Excellent communication skills both written and verbal.
• Self-starter and able to work in a collaborative and results-oriented environment.
• Ability to travel domestically and internationally (5-15%)
• Able to view live and recorded surgical procedures.
• Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role.
• Mandatory Notices
• U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status.
• We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.
• Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississipp

Benefits

Additional Information

Primary Function The AI Research group within Intuitive Surgical has an immediate opening in Sunnyvale, CA for a Machine Learning Engineer with focus on physical AI systems, robotics simulation environments and end-to-end ML pipelines, contributing to new technology development for next-generation robot-assisted surgery platforms.

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