AI Scientist- Dept. of Plastic Surgery

Cleveland Clinic Foundation; Cleveland (OH); On-site; USD 150,000 - 210,000; Full time

Job summary

Cleveland Clinic seeks a Senior or Staff Machine Learning Scientist to develop and translate AI solutions across surgery, perioperative care, clinical research, and healthcare operations.

Embedded in the Department of Plastic Surgery and InSITE Research Group, the role collaborates with surgeons, clinicians, and enterprise AI teams to deliver clinically validated AI from data to deployment.

Qualifications

• PhD in computer science, engineering, data science, biomedical informatics, robotics, applied mathematics or related field.
• Advanced knowledge of ML and deep learning with ability to design rigorous experiments.

Responsibilities

• Design, develop, and validate ML models for surgical, perioperative, clinical, and operational use.
• Advance computer vision, multimodal learning, generative AI, predictive modeling, and real-time clinical decision support.
• Develop ML systems using surgical video, imaging, physiologic signals, sensor data, robotics, EHR data, and patient-reported outcomes.
• Create methods to recognize surgical phases, anatomy, instruments, events, workflow, and OR state.
• Build reusable infrastructure for multimodal data ingestion, labeling, dataset versioning, and deployment.

Skills

PhD in quantitative field

Python & ML frameworks

Real-world data ML

Communication with clinicians

Independent problem-solving

Education

PhD or equivalent in quantitative field

Tools

PyTorch

TensorFlow

JAX

Hugging Face

Job description

Cleveland Clinic is seeking a Senior or Staff Machine Learning Scientist to develop and translate advanced AI solutions across surgery, perioperative care, clinical research, and healthcare operations.

Embedded within the Department of Plastic Surgery and InSITE Research Group, this individual will work directly with surgeons, clinicians, and investigators while collaborating with enterprise AI, engineering, analytics, cloud, and MLOps teams. The role offers a distinctive opportunity to develop AI for the operating room and perioperative environment using surgical video, medical imaging, physiologic signals, sensor data, robotics, electronic health record data, and patient-reported outcomes.

We are seeking a scientist with deep expertise in computer vision, video understanding, or multimodal machine learning, complemented by experience in at least one adjacent area such as generative AI, robotics, predictive modeling, or clinical natural language processing. The successful candidate will contribute across data engineering, model development, rigorous evaluation, clinical validation, and production deployment, helping move high-value projects from clinical need to scalable implementation.

Key Responsibilities

• Design, develop, and validate machine learning models for surgical, perioperative, clinical, and operational applications.
• Advance computer vision, multimodal learning, generative AI, predictive modeling, and real-time clinical decision support.
• Develop machine learning systems using time-synchronized surgical video, medical imaging, physiologic waveforms, device and sensor streams, robotic telemetry, longitudinal electronic health record data, and patient-reported outcomes.
• Create methods to recognize surgical phases, anatomy, instruments, events, workflow, and the evolving state of the operating room.
• Build and extend reusable technical infrastructure for surgical intelligence, including multimodal data ingestion and synchronization, data quality controls, annotation and labeling workflows, dataset versioning, reproducible training pipelines, model evaluation, prospective validation, deployment, and post-deployment monitoring.
• Explore physical AI applications that connect perception, prediction, and action through intelligent surgical systems, robotics, sensor-enabled environments, and human-machine collaboration.
• Collaborate on emerging approaches such as world models, vision-language-action models, and reinforcement learning for surgical and perioperative environments.
• Develop AI solutions addressing surgical safety, quality, patient-reported outcomes, operations, documentation, and perioperative efficiency.
• Translate clinical and operational needs into technically rigorous projects with clear data requirements, validation strategies, and measures of success.
• Provide technical leadership across multidisciplinary projects by shaping system architecture, establishing evaluation standards, reviewing technical work, and coordinating clinicians, researchers, data engineers, ML engineers, enterprise platform teams, and external collaborators from early development through implementation.
• Contribute to peer-reviewed publications, presentations, grants, and collaborative research.
• Apply responsible and human-centered AI practices throughout development and clinical translation, including privacy-preserving data use, bias and subgroup evaluation, interpretability appropriate to the use case, uncertainty communication, human-factors assessment, documentation, and clearly defined human oversight.

Required Qualifications

• PhD in computer science, engineering, data science, biomedical informatics, robotics, applied mathematics, statistics, or a related quantitative field.
• Advanced knowledge of machine learning and deep learning, with demonstrated depth in at least one relevant technical area and the ability to select appropriate methods, design rigorous experiments, diagnose failure modes, and evaluate whether model performance is sufficient for the intended clinical or operational use.
• Strong proficiency in Python and demonstrated ability to develop maintainable, tested machine learning software using modern deep learning frameworks such as PyTorch, TensorFlow, or JAX; experience with relevant model and data ecosystems, including Hugging Face where appropriate.
• Demonstrated experience developing and validating machine learning models using complex real-world data.
• Ability to communicate effectively and collaborate with clinicians, researchers, engineers, and operational leaders.
• Strong record of independent technical problem-solving and multidisciplinary teamwork.

Preferred Qualifications

• Experience with surgical video, medical imaging, physiologic signals, sensor fusion, robotic systems, electronic health record data, or patient-reported outcomes.
• Experience developing models for real-time or safety-sensitive environments.
• Experience with temporal modeling, surgical phase recognition, or human-machine interaction.
• Experience with cloud AI platforms, Databricks, scalable data pipelines, or distributed computing.
• Experience with MLOps, including model deployment, monitoring, reproducibility, and lifecycle management.
• Experience translating AI research into clinical, operational, or other real-world environments.
• Familiarity with responsible AI, privacy, security, data governance, and validation in regulated settings.
• Strong publication, applied research, or AI product development record.
• Experience coordinating engineers, data scientists, or external technical collaborators.

The Ideal Candidate

The ideal candidate is an accomplished AI scientist who wants to work closely with surgeons and clinical teams on consequential healthcare problems. This individual will bring recognized expertise in a core technical discipline while remaining versatile enough to contribute across modeling, multimodal data infrastructure, validation, deployment, and research.

The successful candidate will be intellectually curious, collaborative, and comfortable working in the operating room and perioperative environment. They will understand that meaningful surgical AI requires more than model performance. It requires clinical immersion, thoughtful integration of multiple data streams, prospective validation, responsible implementation, and effective human-machine interaction.

Why Join Us

• Develop AI directly within the operating room and perioperative environment.
• Advance computer vision, multimodal AI, physical AI, surgical intelligence, and personalized decision support
• Build intelligent systems integrating surgical video, imaging, physiologic, sensor, robotic, and clinical data.
• Shape emerging applications of robotics, embodied intelligence, and human-machine collaboration in surgery.
• Develop AI across the continuum from research concept to clinical or operational implementation.
• 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.

Cleveland Clinic is committed to using AI to improve patient outcomes, personalize care, reduce administrative burden, and increase healthcare efficiency. Our AI culture emphasizes technical excellence, curiosity, collaboration, responsible innovation, and measurable clinical impact.