Machine Learning Research Scientist/Engineer

Responsibilities

• Research, develop, and deploy real-time, low-latency surgical AI solutions using state-of-the-art AI technologies.
• Develop and integrate AI Agent and/or deep reinforcement learning (DRL) frameworks for intelligent decision-making, workflow automation, or adaptive optimization in intraoperative video.
• Stay current with the latest developments in AI research and emerging technologies.
• Understand clinical needs to solve real-world problems and drive the design, development, and validation of new AI clinical solutions.
• Conform to the company’s standard procedures of product development.
• Efficiently communicate with project managers and team members on execution.
• Perform other job responsibilities as assigned by management.

Qualifications

• Experience with advanced VLM/SFM/LLM models (e.g., GPT-4o, UniSurg/SurgMotion, SAM) for intraoperative video analysis.
• Experience and skills in working with deep reinforcement learning and/or AI Agent frameworks, including prompt engineering, LangChain/LlamaIndex, or RAG.
• Experience with NVIDIA stacks and hardware deployment is a plus.
• Strong foundational knowledge in geometric computer vision (camera calibration, SLAM, registration, multi-view geometry) and deep learning (classification, tracking, mapping, transformers/CNNs).
• Minimum of 3 years of experience in AI, ML, DL, or related fields.
• Excellent software engineering skills using C/C++; Python, PyTorch, TensorFlow, and Keras preferred.
• Strong problem-solving skills with the ability to rapidly implement, verify, and iterate on solutions.
• Collaborative team player who is highly self-motivated, with a proven ability to learn quickly and thrive in dynamic, high-impact environments.
• Clear communication skills in English.
• PhD in AI/ML/CS or related field, or a master’s degree with a minimum of 3 years of industry experience.

Desired Qualifications

• Strong algorithm development skills with in-depth knowledge of medical image analysis/segmentation and image registration.
• Experience with TensorRT and/or 3D visualization programming in Linux.
• Knowledge of human anatomy and interpretation of medical images.
• Hands-on experience and knowledge in DICOM is a plus.
• Experience working with medical imaging modalities (Endoscopic video, Ultrasound, CT) or similar sensor data is preferred.