Senior/Staff Machine Learning Scientist

Quick Facts

• Role: Senior/Staff Machine Learning Scientist (AI)

• Focus areas: surgery, perioperative care, clinical research, healthcare operations

Description

Develop and translate advanced AI solutions embedded in the Department of Plastic Surgery, working with surgeons, clinicians, investigators, and enterprise AI teams. Build computer vision and multimodal machine learning systems for surgical video, medical imaging, physiologic signals, sensor/robotics telemetry, EHR data, and patient-reported outcomes. Move projects from clinical need through data engineering, model development, evaluation, clinical validation, and production deployment.

Responsibilities

• Design, develop, and validate ML models for surgical, perioperative, clinical, and operational applications

• Advance computer vision, multimodal learning, generative AI, predictive modeling, and real-time clinical decision support

• Build systems for recognizing surgical phases, anatomy, instruments, events, workflow, and OR state

• Create reusable infrastructure for multimodal data ingestion/synchronization, labeling, dataset versioning, reproducible training, evaluation, prospective validation, deployment, and monitoring

• Explore physical AI for perception-prediction-action and human-machine collaboration in surgery

• Work on emerging approaches such as world models, vision-language-action models, and reinforcement learning for surgical/perioperative environments

• Develop AI addressing surgical safety, quality, patient-reported outcomes, operations, documentation, and perioperative efficiency

• Translate clinical/operational needs into technically rigorous projects with validation strategies and success measures

• Provide technical leadership across multidisciplinary teams and collaborators

• Contribute to peer-reviewed publications, presentations, and grants

• Apply responsible, human-centered AI including privacy-preserving data use, bias/subgroup evaluation, interpretability, uncertainty communication, human-factors assessment, documentation, and defined human oversight

Requirements

• PhD in a relevant quantitative field (computer science, engineering, data science, biomedical informatics, robotics, applied mathematics, statistics, or related)

• Advanced machine learning/deep learning knowledge with demonstrated depth in a relevant technical area; ability to select methods, design rigorous experiments, diagnose failure modes, and judge whether performance meets clinical/operational needs

• Strong proficiency in Python and ability to develop maintainable, tested ML software using modern deep learning frameworks

• Experience with relevant model and data ecosystems (e.g., Hugging Face where appropriate)

• Demonstrated experience developing and validating ML models using complex real-world data

• Ability to communicate effectively and collaborate across clinical, research, engineering, and operations stakeholders

• Strong independent technical problem-solving and multidisciplinary teamwork

Benefits

• Develop AI directly in the operating room and perioperative environment

• Advance surgical intelligence, personalized decision support, and intelligent systems integrating multiple clinical and operational data streams

• Build platforms that can extend across projects, procedures, and specialties

• Collaborate with leading clinical, research, enterprise AI, engineering, and external technology teams

• Combine publication-quality research with meaningful clinical impact