4 Nifti Jobs

You will play a crucial role in revolutionizing medical image diagnostics by providing intelligent, ethical, and patient-centric care. We are seeking individuals with a passion for innovation and problem-solving capabilities. You should be able to empathize with consumers, address business challenges, and develop intelligent solutions. Previous experience in handling medical imaging data from various sources is essential, including a deep understanding of different image modalities such as DICOM. Proficiency in DICOM standards for imaging, communication, and reporting is a key requirement. Collaboration with annotation and PACS teams, alongside performing image preprocessing and enhancements, will be at the core of your responsibilities. Your main responsibilities will include building DICOM data pipelines, integrating them with PACS, viewers, and EMRs. You will ensure data retrieval and collation from various databases in compliance with DICOM standards. Understanding metadata, image compression, and seamless transition of parameters from DICOM to NIFTI are crucial. Your role will involve eliminating viewer and acquisition-dependent variables between image series, ensuring data homogeneity for AI model processing. Additionally, you will preprocess and enhance images, integrate AI diagnosis analyses, and work on DICOM SEG and DICOM SR nuances. Your skills and qualifications should include a strong grasp and hands-on experience with DICOM as an imaging standard, communication protocol, and reporting format. Familiarity with different medical imaging formats, DICOM SEG, and DICOM SR is required. You should possess knowledge of manufacturer-specific and machine-specific imaging differences and methodologies to resolve them. Proficiency in DICOM communication standards, DICOMWeb, and data transfer protocols is necessary. Experience with libraries like Pydicom, nibabel, SimpleITK, dcmqi, and dcm2niix will be advantageous. Moreover, you should have a comprehensive understanding of DICOM and NIFTI metadata, as well as medical imaging tests like MRI and CT. Knowledge of interoperability frameworks such as FHIR and HL7 is a plus. Strong communication, analytical, and problem-solving skills are essential, with an eagerness to adapt to new technologies. Your educational background should include a BE/B Tech degree.,

We are seeking a skilled AI/ML Engineer to develop and integrate advanced deep learning solutions into our medical imaging platform. You will work on high-impact use cases such as analyzing MRI scans to assist in Alzheimer's prediction and diagnosis, ensuring your models meet clinical accuracy and performance standards. Key Responsibilities: Develop and fine-tune deep learning models (CNNs, ANNs, Transformers) for medical image classification, segmentation, and anomaly detection. Handle medical imaging data formats (e.g., DICOM, NIfTI) for preprocessing and feature extraction. Integrate trained AI models into existing medical imaging platforms using industry-standard deployment pipelines. Collaborate with radiologists, data scientists, and software engineers to validate model performance and usability. Implement model monitoring and update strategies post-deployment to ensure reliability and compliance. Document methodologies, model architecture decisions, and deployment workflows. Required Skills & Qualifications: 4+ years of experience in AI/ML , with at least 2 years focused on medical or biomedical image processing . Strong hands-on experience with deep learning frameworks : TensorFlow , PyTorch , Keras . Proficient in Python , with good working knowledge of SQL for data management. Experience working with medical imaging libraries and toolkits such as MONAI , OpenCV , SimpleITK , and scikit-image . Familiarity with cloud-based AI deployment tools and services on AWS , GCP , or Azure . Solid understanding of image annotation , model evaluation metrics (e.g., Dice coefficient, ROC-AUC) , and regulatory implications in healthcare AI. Preferred Skills (Nice to Have): Experience with federated learning, explainable AI (XAI), or multimodal learning in healthcare. Exposure to containerization (Docker) and MLOps practices for scalable AI deployments. Familiarity with PACS systems , FHIR , or integration with HL7 standards . Knowledge of FDA/CE regulatory requirements for AI in medical devices.

We are seeking a skilled AI/ML Engineer to develop and integrate advanced deep learning solutions into our medical imaging platform. You will work on high-impact use cases such as analyzing MRI scans to assist in Alzheimer's prediction and diagnosis, ensuring your models meet clinical accuracy and performance standards. Key Responsibilities: Develop and fine-tune deep learning models (CNNs, ANNs, Transformers) for medical image classification, segmentation, and anomaly detection. Handle medical imaging data formats (e.g., DICOM, NIfTI) for preprocessing and feature extraction. Integrate trained AI models into existing medical imaging platforms using industry-standard deployment pipelines. Collaborate with radiologists, data scientists, and software engineers to validate model performance and usability. Implement model monitoring and update strategies post-deployment to ensure reliability and compliance. Document methodologies, model architecture decisions, and deployment workflows. Required Skills & Qualifications: 4+ years of experience in AI/ML , with at least 2 years focused on medical or biomedical image processing . Strong hands-on experience with deep learning frameworks : TensorFlow , PyTorch , Keras . Proficient in Python , with good working knowledge of SQL for data management. Experience working with medical imaging libraries and toolkits such as MONAI , OpenCV , SimpleITK , and scikit-image . Familiarity with cloud-based AI deployment tools and services on AWS , GCP , or Azure . Solid understanding of image annotation , model evaluation metrics (e.g., Dice coefficient, ROC-AUC) , and regulatory implications in healthcare AI. Preferred Skills (Nice to Have): Experience with federated learning, explainable AI (XAI), or multimodal learning in healthcare. Exposure to containerization (Docker) and MLOps practices for scalable AI deployments. Familiarity with PACS systems , FHIR , or integration with HL7 standards . Knowledge of FDA/CE regulatory requirements for AI in medical devices.

AI/ML Engineer for Medical Image processing Job description We are looking for an AI/ML Engineer to join our team and help integrate AI-driven image analysis into an existing medical imaging platform. This role involves developing or integrating AI models to analyze medical images (e.g., MRI brain scans for Alzheimers prediction). Key Responsibilities: Develop and optimize deep learning models (CNNs, Transfer Learning, TensorFlow, PyTorch) for medical image analysis. Work with medical imaging datasets (DICOM, NIfTI, etc.) to extract meaningful insights. Integrate AI models into the imaging platform and ensure seamless deployment. Required Skills: Strong expertise in Deep Learning (CNN, ANN, Transformers, TensorFlow, PyTorch, Keras). Experience with image processing libraries (OpenCV, MONAI, scikit-image). Proficiency in Python, SQL, and cloud-based AI deployment (AWS/GCP/Azure). Experience: 4 years in AI/ML with a focus on image analysis Industry: Healthcare AI / Medical Imaging If you are passionate about AI for medical imaging and want to work on cutting-edge healthcare AI solutions, wed love to hear from you! Apply now or DM me for more details! Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote