Edge AI Engineer - Medical Devices & Computer Vision (Pune)

Role Overview: As an Edge AI Engineer specializing in Medical Devices & Computer Vision, you will play a crucial role in developing and optimizing AI-powered medical devices that operate at the edge. Your expertise in Edge AI devices, computer vision algorithms, and AI model deployment in the MedTech domain will be essential in ensuring the performance, reliability, and compliance of these devices 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. Qualifications Required: - Bachelors or Masters 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. - Strong AI/ML acumen with a crucial understanding of LLM, RAG, and agentic architecture. - 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. Additional Company Details: The company is focused on developing cutting-edge AI solutions for medical devices, emphasizing compliance with regulatory standards and quality processes. They value collaboration and effective communication among cross-functional teams to ensure the successful integration of AI solutions into embedded systems. The ideal candidate would have experience in testing or developing AI systems for surgical applications and possess knowledge of risk management processes and cybersecurity standards in healthcare.,