The Department of Medicine, Division of Nephrology Quantitative Health is seeking a Research Software Engineer IV to support a federally funded, multi-institutional research initiative focused on integrating electronic health records (EHR), histology, and imaging data for predictive modeling in biomedical research. The role aims to lead the development of secure, scalable, and reproducible machine learning (ML) pipelines and software components for AI tool deployment in a research setting.
Requirements
- Experience building and maintaining ML/AI pipelines for multimodal biomedical data
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Familiarity with MLOps tools (e.g., MLflow, Weights & Biases)
- Experience with Docker, Kubernetes, and cloud deployment
- Knowledge of secure software design and research data governance
- Strong technical documentation, version control, and testing skills
- Additional technical certifications (e.g., AWS, Security+, etc.) may be encouraged but not required.
Responsibilities
- Lead the development of scalable and reproducible machine learning pipelines to support training, validation, and deployment of AI models using multimodal biomedical data.
- Design workflows that enable integration of EHR, imaging, and molecular datasets.
- Apply best practices in modular software design to ensure code maintainability and system extensibility.
- Architect secure infrastructure for deploying ML models using containerization (e.g., Docker, Kubernetes) and compatible with institutional computing environments.
- Ensure all software components meet cybersecurity and performance standards for research systems.
- Implement APIs and services to support integration of models into front-end tools or external systems.
- Manage source control (e.g., Git), maintain continuous integration workflows, and implement automated testing pipelines.
Other
- A Bachelor’s Degree in computer or physical science, statistics, bioinformatics, analytics, or similar field and seven years of experience; Master’s Degree in computer or physical science, software engineering, statistics, bioinformatics, analytics, or similar field and five years of experience; Doctoral Degree in computer or physical science, statistics, bioinformatics, analytics, or similar field and three years of experience.
- Collaborate with investigators, clinical researchers, and software engineers to define technical requirements and align model development with research objectives.
- Translate clinical and research needs into engineering solutions through iterative development and testing.
- Participate in team meetings, planning discussions, and user feedback sessions.
- Provide informal guidance to junior developers, students, or collaborators on ML coding practices and system design.
