Senior AI​/ML Research Engineer

Job Description

Primary Function of Position

We are building advanced augmented dexterity capabilities for next-generation robotic platforms. As a Senior AI/ML Research Engineer (Computer Vision), you will develop the perception models that let our Embodied-AI system understand the surgical scene. Working within a hierarchical, multimodal stack—where a high-level model interprets sensory observations into structured intent and a low-level policy turns that intent into precise, safe, real-time control—you will focus on the vision layer: designing, training, and evaluating models that extract anatomy, instruments, actions, and surgical context from intraoperative video.

You will partner with the broader AI/ML team to define how perception feeds reasoning and control, and you will drive the research-to-deployment path for your models, taking them from offline experimentation to robust, real-time performance in the OR.

Working within Intuitive's Future Forward research organization, you will identify, build and finetune the AI/ML models and algorithms that enables us to deliver safe and performant embodied AI systems. This role calls for someone who is equally comfortable getting hands-on with models and data and designing systems that scale.

Roles and Responsibilities

• Develop temporal models for activity and workflow understanding: event/state recognition and fine-grained temporal action segmentation.
• Benchmark in-house models against the state of the art and recommend the target perception architecture.
• Define the perception input/output specification and demonstrate offline feasibility on recorded data.
• Stand up a continuous-improvement loop (discrepancy flagging, active learning, human-in-the-loop relabeling) and the tooling/UI needed for offline evaluation and the path to real-time use.
• Partner with annotation and data teams to shape label taxonomies, QC, and the data pipeline that feeds the AI/ML models.
• Establish the path from offline evaluation on recorded data to real-time integration, including the continuous-improvement (human-in-the-loop) data loop.
• Partner with AI/ML researchers, robotics, data engineers, and other stakeholders to deliver a perception layer that enables rapid prototyping and learning while working toward a product solution.