About the Role:

We are seeking an experienced and passionate Data Scientist with deep expertise in deep learning, medical imaging, and hands-on experience with foundation models. This is a technical contributor role where you will work at the intersection of healthcare and artificial intelligence, building innovative AI solutions that transform medical diagnostics, workflows, and patient outcomes. You will play a key role in designing and developing cutting-edge AI/ML algorithms for image analysis, segmentation, classification, anomaly detection, and generative tasks in Magnetic Resonance Imaging (MRI). Project roles and responsibilities

Key Responsibilities:

- Lead end-to-end development of deep learning models for medical imaging tasks - from data curation and preprocessing to model training, evaluation, and deployment.

- Explore and fine-tune foundation models (e.g., vision transformers, multimodal models like CLIP, BioGPT, MedSAM) for use in diagnostic and clinical imaging applications.

- Drive research and prototyping of novel architectures for image segmentation, detection, and generation (e.g., UNet variants, GANs, autoencoders, diffusion models).

- Collaborate cross-functionally with radiologists, product managers, software engineers, and regulatory teams to ensure clinical relevance, robustness, and compliance.

- Contribute to the development of scalable ML pipelines, model interpretability tools, and performance monitoring systems.

- Publish findings in peer-reviewed journals or conferences and represent the company at scientific and industry forums.

- Mentor junior data scientists and guide the team on best practices in model development, validation, and documentation.

- Goals and deliverables

Required Qualifications:

- PhD or master's degree in computer science, Biomedical Engineering, Applied Mathematics, or a related field.

- 5+ years of experience in data science or machine learning, with at least 3 years focused on medical imaging.

- Strong experience in deep learning frameworks (TensorFlow, PyTorch) and model architectures for computer vision.

- Practical exposure to foundation models, including prompt engineering, fine-tuning, and domain adaptation.

- Proven ability to work with 2D/3D imaging datasets (DICOM, NIfTI), and medical imaging toolkits (e.g., MONAI, SimpleITK, ITK-SNAP).

- Expertise in evaluation metrics specific to medical imaging (Dice, IoU, AUC, etc.) and experience working with imbalanced datasets.

- Solid understanding of healthcare data compliance (HIPAA, FDA, MDR) and medical device AI/ML lifecycle.

- Excellent problem-solving, communication, and leadership skills.

Preferred Qualifications:

- Publications or patents in AI for healthcare or medical imaging domains.

- Experience with PACS/RIS systems, HL7/DICOM standards, and clinical workflows.

- Familiarity with LLMs or multimodal generative models in a clinical context.

- Exposure to MLOps, model deployment, and on-device inference optimisation (e.g., TensorRT, ONNX, OpenVINO).

Pro

Follow Up

Didn’t find the job appropriate? Report this Job

Posted By

Chandra

Managing Partner at Chaitra Soft

Last Active: NA as recruiter has posted this job through third party tool.

Job Views:
201

Applications: 20

Recruiter Actions: 0

Posted in

IT & Systems