Edge AI Engineer – Medical Devices

4 days ago

Remote, India Codvo Full time ₹ 15,00,000 - ₹ 28,00,000 per year

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 and cybersecurity standards in healthcare.
  • Experience with cloud-edge integration and CI/CD pipelines for AI deployment.

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