VAYUZ Technologies

4 weeks ago

Bengaluru, India VAYUZ Technologies Full time

We are looking for an experienced and passionate Data Scientist with strong expertise in deep learning, medical imaging, and foundation models.

This is a hands-on technical contributor role at the intersection of healthcare and artificial intelligence.

You will help build transformative AI solutions to improve diagnostics, clinical workflows, and patient outcomes.

Your work will focus on designing and developing cutting-edge AI/ML algorithms for tasks such as image analysis, segmentation, classification, anomaly detection, and generative modeling in Magnetic Resonance Imaging (MRI).

Project Roles and Responsibilities :

Key Responsibilities :

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

- Explore and fine-tune foundation models (e.g., Vision Transformers, CLIP, BioGPT, MedSAM) for diagnostic and clinical imaging use cases.

- Research and prototype novel architectures for segmentation, detection, and generation (e.g., UNet variants, GANs, Autoencoders, Diffusion Models).

- Collaborate with cross-functional teams including radiologists, product managers, software engineers, and regulatory experts to ensure clinical accuracy, robustness, and compliance.

- Develop scalable ML pipelines, model interpretability tools, and performance monitoring systems.

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

- Mentor junior data scientists and promote best practices in model development, validation, and documentation.

Required Qualifications :

- PhD or Masters degree in Computer Science, Biomedical Engineering, Applied Mathematics, or related field.

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

- Strong hands-on experience with TensorFlow, PyTorch, and deep learning architectures for computer vision.

- Practical knowledge of foundation models, including prompt engineering, fine-tuning, and domain adaptation.

- Experience working with 2D/3D imaging datasets (DICOM, NIfTI) and medical imaging toolkits (e.g., MONAI, SimpleITK, ITK-SNAP).

- Solid understanding of evaluation metrics like Dice, IoU, AUC, and experience handling imbalanced datasets.

- Familiarity with healthcare data compliance (HIPAA, FDA, MDR) and AI/ML lifecycle for medical devices.

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

Preferred Qualifications :

- Research publications or patents in healthcare AI or medical imaging.

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

- Familiarity with LLMs or multimodal generative models in clinical settings.

- Exposure to MLOps, model deployment, and optimization tools such as TensorRT, ONNX, OpenVINO.


(ref:hirist.tech)

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