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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Research Engineer (Computer Vision) - **Company:** Embodied, Inc. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, C++ (Programming Language), Software Debugging, Python (Programming Language), Machine Learning, Rapid Prototyping Process, Tensorflow, Pytorch, Deep Learning, TensorRT, Software Coding, Data Pipelines - **Published:** September 11, 2026 - **Apply:** https://startup.jobs/senior-ai-ml-research-engineer-intuitive-10037565 ## About the Role * MS or PhD in CS, EE, Robotics, or a related field, with 5+ years of applied computer-vision research experience. * Strong grasp of modern CV and deep-learning fundamentals: CNNs and vision transformers, segmentation, detection, tracking, and representation/self-supervised learning. * Demonstrated work in video understanding, including temporal action segmentation, action/phase recognition, and video segmentation. * Hands-on experience with modern video architectures, including video transformers and self-supervised video pretraining. * Exposure to vision-action (VA) / vision-language-action (VLA) models and world-model / self-supervised predictive architectures (e.g., JEPA-style models, MAE, DINO) for learning visual representations and dynamics. * Experience working with large, messy, real-world video datasets at scale. * Strong software and experimentation skills in Python and C++, with proficiency in one or more of PyTorch/TensorFlow/JAX, and the ability to stand up clean, reproducible experiments and run the full loop (data curation, augmentation, loss design, metrics, error analysis). * A research-and-prototyping mindset: comfortable working in ambiguity, framing open-ended problems, running rapid experiments, and reading and reproducing recent papers to pull promising techniques into practice. * Sound judgment about the path from prototype to product: writing code others can build on, knowing when to optimize versus when to move fast, and thinking ahead about data quality, evaluation, and robustness even at the research stage. * Solid foundations in linear algebra, probability, and optimization, enough to reason about and debug model behavior from first principles. * Comfort collaborating across a multidisciplinary team (ML, robotics, software, and clinical/domain experts) and communicating tradeoffs and findings clearly., * Background in healthcare, medical devices, surgical robotics, or other regulated technical domains. * Sim-to-real workflows and experience with robotics simulators (e.g., NVIDIA Isaac) * Experience with structured, ontology- or taxonomy-based labeling frameworks for fine-grained activity. * Multimodal fusion of video with sensor, telemetry, and system-log streams. * Designing annotation pipelines, QC processes, and active-learning loops. * Real-time / edge inference optimization (e.g., TensorRT, NVIDIA Jetson). * Fine-grained interaction and object-relationship modeling. * Relevant peer-reviewed publications (CVPR, ICCV, ECCV, NeurIPS, etc.). 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. ## Description 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. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Robots 2.0: When artificial intelligence meets steel](https://www.wearedevelopers.com/videos/1452-robots-2-0-when-artificial-intelligence-meets-steel) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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