Job Description

Design, develop, and maintain digital pathology and medical imaging software solutions, adhering to DICOM and related standards. Integrate and optimize AI/machine learning models within imaging workflows for tasks such as classification, segmentation, or feature extraction. Collaborate with cross-functional teams, including data scientists, clinicians, and product managers, to gather requirements and deliver high-quality solutions. Develop and support robust pipelines for image data ingestion, secure storage, retrieval, visualization, and analysis. Work with large-scale clinical and research imaging datasets, ensuring data integrity, compliance, and performance. Utilize and extend industry-standard imaging libraries and toolkits such as pydicom, OpenSlide, and ITK. Implement and maintain comprehensive software documentation, tests, and quality assurance processes. Participate in peer code reviews to ensure coding standards and best practices. Stay current with industry trends, new standards such as DICOMweb, and emerging technologies in digital pathology and AI. Contribute to the continuous improvement of engineering processes, including CI/CD pipelines and containerization strategies. Support troubleshooting, debugging, and resolution of image data and software-related issues. Ensure compliance with healthcare regulations and standards regarding data security and software quality.Mandatory Skills: Strong programming proficiency in Python. Solid understanding of DICOM and/or digital pathology standards such as WSI, DICOMweb, and HL7. Experience with medical imaging libraries or toolkits such as pydicom and OpenSlide. In-depth knowledge of AWS services, including but not limited to EC2, S3, Lambda, RDS, IAM, CloudFormation, and API Gateway. Familiarity with database technologies, whether SQL or NoSQL, for imaging data management. Experience working with large-scale image datasets, including secure storage and efficient retrieval. Understanding of version control systems such as Git. Strong skills in technical documentation and producing maintainable code. Ability to work effectively in a collaborative, multidisciplinary team environment. Excellent written and verbal communication skills.Preferred Skills: Experience developing, integrating, or deploying AI/machine learning models for medical imaging tasks such as image classification, segmentation, or feature extraction. Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of annotation tools and data formats commonly used in pathology and imaging datasets. Experience with containerization technologies such as Docker and Kubernetes, along with cloud engineering practices. Understanding of continuous integration/continuous deployment (CI/CD) pipelines and automated testing frameworks. Prior work on whole slide imaging (WSI) workflows and digital pathology image viewers.Educational Requirements: Bachelors or masters degree in computer science or an IT-related discipline with at least 8 years of experience in the IT industry.