AI Research Intern

Primary Function of Position
We are seeking a self-motivated intern to support our AI Research and Development team in projects focused on developing a variety of AI foundation models based on multi-modal surgical data. This unique role focuses on the application of cutting-edge Visual-Language-Action (VLA) models and advanced robot learning techniques to enhance the capabilities of the da Vinci surgical system. The ideal candidate will bridge the gap between large-scale multimodal AI research and practical, high-impact applications in a safety-critical medical domain.
Essential Job Duties
Conduct research and development on AI technology for surgical robotics, specifically integrating visual data (endoscopic video), surgical context (language/data), and precise robotic actions (instrument control).
Develop and implement novel algorithms for VLA models focused on surgical scene understanding, procedure phase recognition, and learning from expert demonstrations (e.g., imitation learning) to improve system guidance and automation features.
Analyze and process large, real-world surgical datasets from the da Vinci system to train and evaluate AI models.
Validate models using both internal simulation platforms and, where appropriate, physical da Vinci systems, adhering to strict quality and regulatory protocols.
Collaborate with a cross-functional team of engineers, researchers, and potentially even clinicians/surgeons, to translate research prototypes into robust, testable software solutions.
Document research outcomes and contribute to technical reports and internal documentation, with potential opportunities for patent filings or conference submissions.
Required Skills and Experience
University Hiring Program Eligibility Requirements:
University Enrollment: Must be currently enrolled in and returning to an accredited degree-seeking academic program in the Fall.
Internship Work Period: Must be available to work starting January 2027 and full-time (approximately 40 hours per week) during a 10-12 week period. Specific start dates are shared during the recruiting process.
Required Education and Training
Current enrollment in an Computer Science, Electrical Engineering or Robotics with emphasis on AI, Machine Learning and Computer Vision or related degree-seeking program at the Master’s or Doctorate level.
Preferred Skills and Experience
Publications in top-tier conferences/journals
Experience building systems based on machine learning and/or deep learning methods.
Strong hands-on Python skills.
Strong hands-on experience with deep learning frameworks such PyTorch, TensorFlow, and Caffe.
Good hands-on experience with the state-of-the-art deep learning models for language modelling and text retrieval of structured and unstructured text.
Good hands-on experience with open-source LLM models and libraries (HuggingFace, LLaMa, LangChain, LlamaIndex, etc).
Self-starter and able to work in a collaborative and results oriented environment.
(Preferred) Experience extending and innovating on LLM/AI agent techniques. Experience in one or more of RLHF, DPO, finetuning, RAG, CoT, and multi-agent reasoning.
(Preferred) Experience with model quantization, LLM edge hardware deployment, prompt engineering, and/or data synthesis.
Robotics, action models, large language models (LLM), visual language models (VLM)

Employment type
Intern

Work arrangement
No