| Classification Title: | Research Software Engineer IV |
|---|
| Classification Minimum Requirements: | A Bachelors Degree in computer or physical science statistics bioinformatics analytics or similar field and seven years of experience; Masters 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. |
|---|
| Job Description: | 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. Essential Functions; AI/ML Pipeline Design and Implementation
- 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. Secure Software Architecture and Deployment
- 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. Version Control Documentation and Testing
- 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). Cross-Functional Collaboration and Requirements Analysis
- 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. Mentorship and Optimization Support
- 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. |
|---|
| Expected Salary: | $82000 - $98000 Annually |
|---|
| Required Qualifications: | A Bachelors Degree in computer or physical science statistics bioinformatics analytics or similar field and seven years of experience; Masters 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. |
|---|
| Preferred: | 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
Experience working in interdisciplinary research teams
Strong technical documentation version control and testing skills
Ability to communicate technical decisions clearly and collaborate across functions
Additional technical certifications (e.g. AWS Security etc.) may be encouraged but not required. |
|---|
| Special Instructions to Applicants: | In order to be considered you must upload your resume. Application must be submitted by 11:55 p.m. (ET) of the posting end date. |
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| Health Assessment Required: | No |
|---|
Classification Title:Research Software Engineer IVClassification Minimum Requirements:A Bachelors Degree in computer or physical science statistics bioinformatics analytics or similar field and seven years of experience; Masters Degree in computer or physical science software engineering statistics ...
| Classification Title: | Research Software Engineer IV |
|---|
| Classification Minimum Requirements: | A Bachelors Degree in computer or physical science statistics bioinformatics analytics or similar field and seven years of experience; Masters 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. |
|---|
| Job Description: | 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. Essential Functions; AI/ML Pipeline Design and Implementation
- 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. Secure Software Architecture and Deployment
- 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. Version Control Documentation and Testing
- 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). Cross-Functional Collaboration and Requirements Analysis
- 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. Mentorship and Optimization Support
- 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. |
|---|
| Expected Salary: | $82000 - $98000 Annually |
|---|
| Required Qualifications: | A Bachelors Degree in computer or physical science statistics bioinformatics analytics or similar field and seven years of experience; Masters 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. |
|---|
| Preferred: | 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
Experience working in interdisciplinary research teams
Strong technical documentation version control and testing skills
Ability to communicate technical decisions clearly and collaborate across functions
Additional technical certifications (e.g. AWS Security etc.) may be encouraged but not required. |
|---|
| Special Instructions to Applicants: | In order to be considered you must upload your resume. Application must be submitted by 11:55 p.m. (ET) of the posting end date. |
|---|
| Health Assessment Required: | No |
|---|
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Job Location:
Yearly Salary:
$ 82000 - 98000
Posted on:
30+ days ago
Vacancies:
1 Vacancy
