Job Description: Edge AI Product Owner Medical Devices & AI.
Experience Level: 5-8 Years.
Department: Product, Data and AI Engineering.
About the Role:
This role requires a deep understanding of medical device compliance, AI technologies, and product strategy to deliver impactful and regulatory-compliant solutions.
Key Responsibilities:
- Define and drive the product vision, roadmap, and strategy for Edge AI-enabled medical devices.
- Collaborate with cross-functional teams including engineering, clinical, regulatory, and quality to ensure product alignment and compliance.
- Oversee the development and integration of computer vision and video-based AI algorithms into edge devices.
- Ensure adherence to SaMD classification, regulatory frameworks (e.g., FDA, MDR), and quality processes.
- Lead verification and validation planning and execution for Edge AI products.
- Gather and prioritize customer and stakeholder requirements to inform product decisions.
- Communicate product goals, progress, and risks effectively to internal and external
stakeholders.
- Support test data validation and performance evaluation of AI models deployed on edge devices.
Required Qualifications:
- Bachelors or Masters degree in Engineering, Computer Science, Biomedical Engineering, or related field.
- 5-8 years of experience in product management or ownership, preferably in medical devices or healthcare technology.
- Strong understanding of Edge AI systems, including device architecture, model deployment, and performance optimization.
- Experience with computer vision and video-based AI technologies.
- Familiarity with SaMD regulations, ISO 13485, IEC 62304, and related standards.
- Proven track record in managing regulated software products through the full product lifecycle.
- Excellent verbal and written communication skills.
- Experience with agile methodologies and product management tools.
Preferred Skills:
- Experience with surgical AI applications and edge device integration.
- Knowledge of risk management processes (ISO 14971, 510).
- Familiarity with cloud platforms (AWS, Azure) and CI/CD pipelines.
- Understanding of data privacy and cybersecurity standards in healthcare.
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