Senior Engineer – Imaging AI

2 weeks ago

Bucharest, Bucureşti, Romania HN Services Romania Full time €60,000 - €80,000 per year

With 42 years of experience in the international market and 19 years in Romania, HN Services means:

  • Digital transformation and IT professionals;
  • Diversity of technical roles;
  • Wide IT market exposure in different domains of activity;
  • A dedicated internal training center for software development.

Main Responsibilities

1. Imaging AI & MONAI

  • Training, validation, and integration of segmentation/classification models using MONAI, nnU-Net, and other OSS frameworks.
  • Exporting results as DICOM SR/SEG and integrating them into PACS clinical workflows.
  • Collaborating with radiologists for feedback and model improvement.

2. PACS & Imaging Integrations

  • Administration and configuration of Orthanc PACS, integration with OHIF Viewer via DICOMweb.
  • Ensuring compatibility with DICOM standards (QIDO/WADO/STOW).
  • Supporting annotation pipelines and clinical workflows.

3. Data Engineering & Interoperability

  • Ingestion and processing of medical data using HL7/FHIR standards.
  • Implementation of ETL/ELT pipelines for Data Lakehouse (Delta/Iceberg).
  • Normalizing and structuring clinical data for BI, ML, and AI.

4. MLOps & Platform Engineering

  • Deployment and serving of models on Kubernetes (on-prem/cloud).
  • CI/CD for AI models and services, observability and monitoring (Langfuse, Prometheus, Grafana).
  • Optimizing inference performance, GPU cost management, and model versioning.

5. Collaboration & Compliance

  • Close collaboration with clinical teams (radiology, genetics, laboratory).
  • Ensuring compliance with security requirements (ISO and AI Act / SaMD regulations.
  • Technical documentation and participation in internal/external audits.

Requirements

  • Education:
    Computer Science, Biomedical Engineering, Mathematics, or similar.
  • Experience:
  • 3–5 years in ML/Deep Learning, preferably in medical imaging.
  • Hands-on experience with PACS (Orthanc) and visualization (OHIF).
  • Experience with medical standards: DICOM, HL7, FHIR.
  • Experience in Data Engineering (ETL, Lakehouse, SQL) and MLOps (K8s, CI/CD).
  • Key Technologies:
  • Python (PyTorch, MONAI, nnU-Net).
  • PACS: Orthanc, OHIF, DICOMweb APIs.
  • Data: Apache Spark, Delta Lake/Iceberg, HL7/FHIR.
  • MLOps: Kubernetes, Docker, GitLab CI/CD, observability (Prometheus/Grafana).

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