AI Research Intern

Job Description

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 role is an exciting opportunity to join a newly formed team, advance the state-of-the-art in surgical robotics, and test your knowledge in a challenging problem-solving environment.

Essential Job Duties

• Research, design and implement AI algorithms using multi-modal data including image, video, text, and robotics.
• Develop software and methods for training, evaluation and testing such AI algorithms.
• Develop evaluation metrics in the context of specific applications and perform extensive validation experiments to analyze accuracy, efficiency, and generalizability.
• Work with existing datasets and contribute to efforts in creating new datasets.

Qualifications

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 October 2024 and full-time (approximately 40 hours per week) during a 10-12 week period starting May or June. 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.