Scientific Software Engineer w/ AI Concentration

The Johns Hopkins Center for Data Science in Emergency Medicine (CDEM) is seeking a dynamic individual for the position of Scientific Software Engineer w/ AI Concentration, with a focus on machine learning, and specifically artificial intelligence (AI).
The successful candidate will be a part of a cutting-edge research software engineering team at Johns Hopkins School of Medicine (JHUSOM), contributing to the advancement of scientific software, and the creation of systems based on novel combinations of human and artificial intelligence and advanced data science methods to improve patient care.
This role utilizes the strengths of scientific computing to drive innovation in high-value target projects identified across all areas of emergency medicine and particularly clinical decision support.

Specific Duties & Responsibilities

• The Scientific Software Engineer with AI concentration will be responsible for collaborating on ground-breaking research projects and clinical decision support tools that demand advanced software solutions.
  
• Designing and building innovative AI solutions for CDEM projects in collaboration with software developers, data scientists, clinicians, and scientific subject matter experts and users.
  
• Utilizing XGBoost, random forest and the latest deep neural network (DNN) libraries trained on state-of-the-art hardware to predict outcomes and forecast time series data.
  
• Working with clinicians and data scientists to analyze massive patient-level data sets and develop software pipelines for real-time high-frequency data processing workflows.
  
• Working closely with internal and external stakeholders to understand interface and backend server needs, envisioning solutions, and developing prototypes and functional requirements.
  

Special Knowledge, Skills & Abilities

• Strong scientific literacy and curiosity, ability to continually adapt to new scientific domains and problems and identify and articulate scientifically informed AI and data analysis approaches.
  
• Strong experience (2+ years) in software development, with a focus on building robust, scalable, and maintainable software solutions.
  
• Prior experience specifically in developing machine learning models, preferably within the healthcare or biomedical domain.
  
• Proficiency in Python programming language, as well as experience with relevant libraries and frameworks like TensorFlow, PyTorch, scikit-learn, and Keras.
  
• Knowledge of Machine Learning and Clinical Decision Support, including solid understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods.
  
• Proficiency in software development best practices, including version control (e.g., Git), unit testing, continuous integration/continuous deployment (CI/CD), and agile development methodologies.
  
• Experience with cloud computing platforms (e.g., AWS, Google Cloud Platform, Azure) and containerization technologies (e.g., Docker, Kubernetes) for deploying and scaling machine learning models.
  
• Strong problem-solving skills and the ability to translate research findings into production-ready software solutions.
  
• Excellent communication skills, both verbal and written, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.
  
• Experience collaborating with interdisciplinary teams, including clinicians, data scientists, and other software engineers, to define requirements, develop solutions, and validate model performance.
  
• Awareness of regulatory requirements governing healthcare software development, such as HIPAA (Health Insurance Portability and Accountability Act) and FDA (Food and Drug Administration) guidelines for medical devices and software.
  
• Understanding of ethical considerations and privacy concerns related to handling sensitive patient data, and a commitment to maintaining data security and confidentiality.
  

• Bachelor's Degree.
  
• Five years related experience.
  
• Additional education may substitute for required experience and additional related experience may substitute for required education, to the extent permitted by the JHU equivalency formula.
  

• Master's Degree or PhD in a quantitative discipline.
  
• Seven or more years of experience in the above areas.
  
• Experience designing and developing advanced scientific data visualizations.
  
• Knowledge of healthcare data standards, such as HL7, DICOM, FHIR, and experience working with electronic health records (EHR) data is highly desirable.
  
• Familiarity with clinical decision support systems, including their design, implementation, and integration into healthcare workflows.
  

Classified Title:
Software Engineer
Role/Level/Range:
ATP/04/PE
Starting Salary Range:
$34.90 - $61.05 HRLY ($47,000 targeted; Commensurate with experience)
Employee group:
Casual / On Call
Schedule:
Varies; 19 Hours/Week
Exempt Status:
Exempt
Location:
Mount Washington Campus
Department name:
SOM Em Med Research
Personnel area:
School of Medicine