Job Title: AI Image Processing Specialist
Location: Remote /JaipurJob Type: Full-time / ContractExperience: 3+ years in computer vision, with medical imaging a plus
Job Summary
We are seeking a highly skilled and detail-oriented
AI Image Processing Specialist
to join our team, with a strong focus on
medical imaging
,
computer vision
, and
deep learning
. In this role, you will be responsible for developing and optimizing scalable image processing pipelines tailored for diagnostic, radiological, and clinical applications. Your work will directly contribute to advancing AI capabilities in healthcare by enabling accurate, efficient, and compliant medical data analysis. You will collaborate with data scientists, software engineers, and healthcare professionals to build cutting-edge AI solutions with real-world impact.
Key Responsibilities
- Design, develop, and maintain robust image preprocessing pipelines to handle various medical imaging formats such as DICOM, NIfTI, and JPEG2000.
- Build automated, containerized, and scalable computer vision workflows suitable for high-throughput medical imaging analysis.
- Implement and fine-tune models for core vision tasks, including image segmentation, classification, object detection, and landmark detection using deep learning techniques.
- Ensure that all data handling, processing, and model training pipelines adhere to regulatory guidelines such as HIPAA, GDPR, and FDA/CE requirements.
- Optimize performance across pipeline stages — including data augmentation, normalization, contrast adjustment, and image registration — to ensure consistent model accuracy.
- Integrate annotation workflows using tools such as CVAT, Labelbox, or SuperAnnotate and implement strategies for active learning and semi-supervised annotation.
- Manage reproducibility and version control across datasets and model artifacts using tools like DVC, MLFlow, and Airflow.
Required Skills
- Strong experience with Python and image processing libraries such as OpenCV, scikit-image, and SimpleITK.
- Proficiency in deep learning frameworks like TensorFlow or PyTorch, including experience with model architectures like U-Net, ResNet, or YOLO adapted for medical applications.
- Deep understanding of medical imaging formats, preprocessing techniques (e.g., windowing, denoising, bias field correction), and challenges specific to healthcare datasets.
- Experience working with computer vision tasks such as semantic segmentation, instance segmentation, object localization, and detection.
- Familiarity with annotation platforms, data curation workflows, and techniques for managing large annotated datasets.
- Experience with pipeline orchestration, containerization (Docker), and reproducibility tools such as Airflow, DVC, or MLFlow.
Preferred Qualifications
- Experience with domain-specific imaging datasets in radiology, pathology, dermatology, or ophthalmology.
- Understanding of clinical compliance frameworks such as FDA clearance for software as a medical device (SaMD) or CE marking in the EU.
- Exposure to multi-modal data fusion, combining imaging with EHR, genomics, or lab data for holistic model development.
- Experience with pipeline orchestration, containerization (Docker), and reproducibility tools such as Airflow, DVC, or MLFlow.
- Ensure that all data handling, processing, and model training pipelines adhere to regulatory guidelines such as HIPAA, GDPR, and FDA/CE requirements.
Why Join Us
Be part of a forward-thinking team shaping the future of AI in healthcare. You’ll work on impactful projects that improve patient outcomes, streamline diagnostics, and enhance clinical decision-making. We offer a collaborative environment, opportunities for innovation, and a chance to work at the cutting edge of AI-driven healthcare.
Skills: docker,u-net,mlflow,containerization,image segmentation,simpleitk,yolo,image processing,computer vision,medical imaging,object detection,tensorflow,opencv,pytorch,image preprocessing,resnet,python,dvc,airflow,scikit-image,annotation workflows
