Minimum Required Experience : 15 years

Full Time

Skills

Clinical Workflows

Mlflow

Kubeflow

Description

Domain Expert – MedTech AI & Digital Health Role overview Field Detail Job title Practice Lead – MedTech AI & Digital Health Role type Domain Expert Reporting to DU Head/Delivery Manager Focus Medical Imaging AI, SaMD, Clinical GenAI, Regulatory Compliance Role objective Lead the MedTech practice in building AI-enabled, regulation-ready medical devices and software, from imaging AI to agentic clinical and regulatory workflows. Key responsibilities • Strategy: Define the MedTech AI roadmap across imaging, monitoring, and point-of-care devices. • Tech hubs: Lead three hubs: Imaging & Computer Vision, Clinical GenAI & Regulatory Intelligence, and Connected Devices & Interoperability. • Compliance: Embed IEC 62304, ISO 13485, ISO 14971, and GMLP into AI delivery; support FDA 510(k) and EU MDR submissions. • Standards: Own the medical AI "Golden Stack" and MLOps practices for validation and traceability. • Accelerators: Build reusable assets, such as regulatory compliance assistants and imaging AI components. • Growth: Drive pre-sales solutioning, client advisory, and thought leadership. Mandatory skills • Experience: 15–20 years total; at least 8 years in MedTech, including 5+ in AI/ML architecture.



• Medical imaging and computer vision: Deep learning for medical images and video (PyTorch, OpenCV). • Production AI deployment: Model optimization and edge inference (ONNX Runtime, TensorRT, OpenVINO). • Regulatory knowledge: IEC 62304, ISO 13485, ISO 14971, FDA 510(k). • Healthcare standards: DICOM, PACS. • Generative AI: LLMs, RAG, and agentic AI in production. • Leadership: Led multi-disciplinary AI teams and senior client stakeholders. Desired skills • Clinical workflows: radiology, cardiology, obstetrics, ultrasound • AI regulation: FDA AI/ML guidance, PCCP, EU MDR, EU AI Act, IEC 81001-5-1 • Interoperability: HL7 v2, FHIR, EHR integration • MONAI, NVIDIA Clara/Holoscan, Orthanc • Cloud healthcare services and MLOps (MLflow, Kubeflow) • Publications, patents, or open-source work in medical AI 2026 tech stack expectations Area Technologies Imaging AI PyTorch, MONAI, YOLO, MedSAM Inference ONNX Runtime, TensorRT, OpenVINO GenAI Llama, Mistral, GPT, Gemini, Claude; LangChain/LangGraph; vector DBs Platform Python, C++, FastAPI, Docker, Kubernetes Education and qualifications Degree or diploma in CS, IT, Electronics, or related field, or equivalent experience.

📌 Software Engineer (Bengaluru)
🏢 NeST Digital
📍 Bengaluru