Senior Data Scientist - AI Engineer

American Radiologist Network Inc is building a diagnostic intelligence platform that advances clinical decision support using state-of-the-art, multimodal imaging models. In this remote role, you will lead end-to-end work that spans academic-level research and production deployment across CT, MRI, X-ray, ultrasound, and multimodal fusion, with a focus on regulatory expectations for medical AI.

• Drive ideation, research, and development of next-generation models across CT
  , MRI
  , X-ray
  , ultrasound
  , and multimodal fusion architectures.
• Lead deep research efforts, including novel model design, benchmarking, ablation studies, and scientific validation.
• Convert research findings into production-ready systems, emphasizing reliability, scalability, and clinical relevance for real-world diagnostic workflows.
• Build and manage pipelines for dataset ingestion, cleaning, labeling, augmentation, multimodal alignment, and large-scale imaging data management.
• Perform expert-level model evaluation, error analysis, robustness testing, and optimization for high-performance inference.
• Ensure workflows meet high regulatory standards for medical AI, including data governance, auditability, and reproducibility.
• Partner with engineering, product, and clinical teams to deliver models that support diagnostic intelligence and clinical decision support.

• Master’s Degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Biomedical Engineering, or a closely related technical field.
• Expert proficiency in Py Torch ,
  Tensor Flow
  , Ultralytics YOLO
  , MONAI
  , and the Hugging Face ecosystem.
• Demonstrated experience with medical imaging datasets
  , DICOM workflows
  , PACS systems
  , and radiology modalities.
• Hands-on experience with dataset curation, annotation, and quality control tools including Fifty One
  , Roboflow
  , Labelbox
  , V7
  , or Encord
  .
• Proven ability to lead research initiatives and publish or present advanced imaging work at academic or industry venues.
• Strong background in segmentation
  , detection
  , multimodal architectures
  , and imaging-specific preprocessing pipelines.
• Experience deploying models using Core ML
  , ONNX Runtime
  , NVIDIA TensorRT/Deep Stream
  , or major cloud ML platforms (
  Azure
  , AWS
  , GCP
  ).
• Solid engineering foundation in Python
  , GPU computing
  , and Docker/Kubernetes for scalable ML systems.
• Familiarity with regulatory frameworks for medical AI, including data privacy
  , auditability
  , and reproducibility standards.

• Machine learning: 5 years (Required)
• DICOM: 3 years (Required)
• AI: 5 years (Required)
• Python: 5 years (Required)
• Clinical information systems: 2 years (Preferred)

• PyTorch, Tensor Flow, Ultralytics YOLO, MONAI, Hugging Face
• Fifty One, Roboflow, Labelbox, V7, Encord
• Core ML, ONNX Runtime, NVIDIA TensorRT, Deep Stream
• Azure, AWS, GCP, Python, Docker, Kubernetes
• DICOM, PACS

• 401(k)
• 401(k) matching
• Dental insurance
• Flexible schedule
• Health insurance
• Paid time off
• Retirement plan
• Vision insurance

• Prior collaboration with radiologists, imaging scientists, or clinical imaging teams.
• Experience building multimodal (vision + text) diagnostic or triage models.
• Experience working in a start-up environment with small teams to develop ideas for global impact.

Location: Remote

Salary: USD 180, per year

Minimum experience: 2 years

Education: Master’s (Required)