Research Software Engineer IV

University of Florida-posted 5 days ago
Full-time
Gainesville, FL
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The Department of Medicine, Division of Nephrology Quantitative Health is seeking a full time Research Software Engineer IV. This position supports a federally funded, multi-institutional research initiative housed within the Computational Microscopy Imaging Lab (CMIL) focused on the integration of electronic health records (EHR), histology, and imaging data for predictive modeling in biomedical research. The Research Software Engineer IV will lead the development of secure, scalable, and reproducible machine learning (ML) pipelines and software components that support AI tool deployment in a research setting. This role requires collaboration with data scientists, clinical researchers, and software developers to ensure modeling systems are maintainable, interoperable, and compliant with institutional and federal standards. The position reports to Dr. Pinaki Sarder, Principal Investigator.

  • 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.
  • Create detailed technical documentation, including system architecture diagrams, model input/output specifications, and usage instructions.
  • Contribute to reproducibility by using and maintaining MLOps tools (e.g., MLflow, Weights & Biases).
  • 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.
  • Lead efforts to improve model performance, interpretability, and reliability through benchmarking and systematic evaluation.
  • A Bachelor’s Degree in computer or physical science, statistics, bioinformatics, analytics, or similar field and seven years of experience; or
  • Master’s Degree in computer or physical science, software engineering, statistics, bioinformatics, analytics, or similar field and five years of experience; or
  • Doctoral Degree in computer or physical science, statistics, bioinformatics, analytics, or similar field and three years of experience.
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