Edge AI Engineer – Medical Devices & Computer Vision

India

Job Description: Edge AI Engineer – Medical Devices & Computer Vision

Experience Level: 5–8 Years

Department: Edge AI & Embedded Systems

About the Role:

We are looking for a highly motivated and technically proficient Edge AI Engineer with a strong background in Edge AI devices, computer vision algorithms, and AI model deployment in the MedTech domain. This role is pivotal in developing and optimizing AI-powered medical devices that operate at the edge, ensuring performance, reliability, and compliance with healthcare standards.

Key Responsibilities:

Design, develop, and optimize AI models for deployment on Edge AI devices in medical applications.
Implement and evaluate computer vision algorithms for real-time video and image analysis.
Collaborate with cross-functional teams to integrate AI solutions into embedded systems and medical devices.
Ensure compliance with SaMD classification, regulatory standards, and quality processes.
Document design specifications, test protocols, and validation reports in accordance with regulatory requirements.
Communicate technical findings and project updates effectively to stakeholders.

Required Qualifications:

Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, Biomedical Engineering, or related field.
5–8 years of experience in AI engineering, preferably in medical devices or healthcare technology.
Strong experience with Edge AI hardware platforms (e.g., NVIDIA Jetson, Google Coral, Intel Movidius).
Proficiency in computer vision frameworks (e.g., OpenCV, TensorFlow, PyTorch) and model optimization tools.
AI/ML Acumen (Crucial) Required: Strong LLM, RAG, agentic architecture understanding
Understanding of SaMD regulations, ISO 13485, IEC 62304, and related standards.
Experience with embedded systems development and real-time processing.
Excellent verbal and written communication skills.

Nice to Have:

Experience testing or developing AI systems for surgical applications.
Familiarity with test data validation for computer vision and video-based AI models.
Knowledge of risk management processes (ISO 14971) and cybersecurity standards in healthcare.
Experience with cloud-edge integration and CI/CD pipelines for AI deployment.

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