Future opportunities - Sr Manager Data Operations, Medical Imaging AI
About The Position
Primary Function of Position The Ion™ endoluminal system is Intuitive's robotic platform for minimally invasive biopsy in the peripheral lung, designed to improve the early diagnosis of lung cancer. The Ion R&D team is looking for an experienced leader to own medical image dataset development. You will build and scale a high-performing organization of internal annotation specialists and external partners, delivering high-quality datasets to enable intelligent capabilities in our robotic platform. In this role, you will work at the intersection of Machine Learning, Clinical and Regulatory Affairs, and Data Operations. You will define organization-wide standards for dataset quality, establish scalable data workflows, and serve as the single accountable owner for dataset readiness across programs. You will directly accelerate the development of AI-powered technologies that help physicians diagnose patients earlier and more accurately.
Requirements
- A bachelor’s degree in computer science, biomedical engineering, or equivalent experience
- Five or more years of experience in data operations or ML dataset management, including experience leading multiple teams or programs
- Experience working with medical imaging data (e.g., CT, X-ray, ultrasound)
- Demonstrated experience managing people and/or external vendors in an operational or technical environment
- Strong project management skills with experience coordinating cross-functional work
- Solid understanding of data quality, documentation, and traceability principles
- Ability to interpret technical requirements and collaborate effectively with ML engineers and clinical experts
- Strong written and verbal communication skills
- High levels of ownership, organization, and attention to detail
Nice To Haves
- Experience working in an FDA-regulated medical device environment (e.g., 510(k), PMA, MDR, ISO 13485)
- Experience writing operating procedures, work instructions, or other quality system documentation
- Familiarity with annotation tools such as SuperAnnotate, Labelbox, CVAT, or similar
- Understanding of AI/ML regulatory guidance (e.g., FDA Good Machine Learning Practice)
Responsibilities
- Define and oversee dataset strategy and execution across multiple programs, balancing competing priorities and timelines
- Translate ML engineering and clinical requirements into clear dataset specifications
- Manage multiple teams of internal labeling technicians, including hiring, onboarding, training, performance management, and day-to-day workload planning
- Procure and manage external annotation vendors and contractors to meet quality and schedule targets
- Track dataset progress and communicate status, risks, and tradeoffs to leadership
- Partner with Regulatory Affairs and Clinical Affairs to ensure datasets meet FDA and international guidelines
- Establish and oversee quality control workflows, acceptance criteria, and rework processes for data annotation
- Define and enforce labeling guidelines, SOP’s, and reviewer instructions in collaboration with ML engineers and clinical SME’s
- Own the creation and maintenance of dataset documentation to support releases and submissions
- Improve data operations workflows, standards, and tooling across teams in partnership with software and data engineering groups
- Serve as the single accountable owner for dataset readiness
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What This Job Offers
Job Type
Full-time
Career Level
Manager
