Hybrid MLOps & AI Integration Engineer

    Location: Gyeonggi-do

    Contract Type: Permanent

    Salary: ₩50,000,000 – ₩100,000,000 per annum

    A foreign medical device company is searching for a Hybrid MLOps & AI Integration Engineer. The selected candidate will be in charge of deploying, optimizing, and integrating AI models into surgical robotic systems.

    Responsibilities:

    • Integrate AI models into surgical robotic systems, ensuring compatibility with control loops and real-time operational requirements
    • Optimise AI inference for edge devices such as NVIDIA IGX, balancing performance, latency, and power constraints
    • Collaborate with robotics engineers to design APIs and interfaces for seamless AI–robot communication
    • Architect and implement ETL/ELT workflows for medical imaging and procedural data, including DICOM and sensor data
    • Build experiment tracking and model registry pipelines with MLflow or Kubeflow
    • Manage hybrid cloud-edge deployments on AWS and on-prem robotic systems using Infrastructure-as-Code
    • Containerise AI services with Docker deploy via Kubernetes (EKS) and establish CI/CD pipelines for model updates to robotic platforms
    • Develop real-time REST/gRPC APIs for AI inference services, robot communication, and integration with clinical systems
    • Implement real-time monitoring for model performance on robots using Grafana and Prometheus with alerts for anomalies
    • Collaborate with QA/RA teams to document safety and effectiveness for medical device compliance, including FDA and CE

    Requirements:

    • Bachelor’s or Master’s in computer science, robotics, or related field
    • More than 4 years of backend development experience (real-time APIs, microservices)
    • More than 2 years in MLOps or ML deployment
    • Hands-on experience deploying AI models to edge devices (e.g., NVIDIA IGX, Jetson)
    • Proficient in Python and at least one of C++ or C# for robotic system integration
    • Experience with Docker, Kubernetes, and CI/CD pipelines for ML workflows
    • Solid understanding of real-time systems, latency optimisation, and control software
    • Preferred requirements:
      • Familiarity with robotic system integration and real-time control loops.
      • Knowledge of medical device compliance and healthcare cybersecurity standards

    About the Company:

    Based in the United States, this international medical device company specialises in the development of innovative endovascular robotic systems.

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