Artificial Intelligence Engineer I
Role details
Job location
Tech stack
Job description
AI/ML Model Development & Deployment
- Collaborates closely with clinical researchers, physicians, and engineering teams to design, build, and deploy machine learning models for healthcare applications.
- Assists in the development of AI-powered solutions spanning genomics analysis, EHR data mining, medical imaging interpretation, and diagnostic support systems.
- Supports robust ML pipelines from research prototypes to production-ready systems in clinical environments.
- Ensures models meet healthcare regulatory standards and maintain high performance in real-world clinical settings.
Technical Implementation
- Assists in the design and implement scalable AI/ML architectures using modern frameworks (TensorFlow, PyTorch, scikit-learn).
- Documents data pipelines for processing complex clinical data from sources like Epic Clarity, REDCap, omics platforms, and medical imaging systems.
- Develops and maintains infrastructure for integrating multi-modal healthcare data (genomics, transcriptomics, proteomics, imaging, EHR).
- Optimizes model performance for deployment on various platforms including cloud infrastructure and edge devices.
- Integrates AI models with existing healthcare IT systems and electronic health records.
Research & Innovation
- Stays current with latest developments in healthcare AI, including applications in precision medicine, computer vision, and natural language processing.
- Collaborates on research publications and presentations at medical and technical conferences.
- Participates in grant proposals and collaborative research initiatives with clinical departments.
- Performs other job-related duties as assigned.
Requirements
We are seeking an innovative AI Engineer I to join our team at the Baylor College of Medicine and Texas Children's Hospital Data Science Center, where cutting-edge artificial intelligence meets healthcare delivery. This position offers a unique opportunity to collaborate and deploy AI/ML models that directly impact patient care and clinical workflows. You'll work at the intersection of multi-omics data, electronic health records, medical imaging, and clinical decision support systems., * Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field or four years of relevant experience may substitute for degree requirement.
- No prior experience required with Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
Department Specific Requirements
- Strong proficiency in Python programming with experience in ML/AI libraries (NumPy, pandas, scikit-learn, TensorFlow/PyTorch).
- Solid understanding of machine learning fundamentals including supervised/unsupervised learning, deep learning architectures, and model evaluation.
- Experience with ML model deployment and production systems.
- Familiarity with version control (Git) and collaborative development workflows.
Preferred Qualifications and Skills
- Background in genomics data processing, bioinformatics pipelines, or clinical informatics.
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Experience working with large-scale omics datasets (RNA-seq, whole genome/exome sequencing, proteomics).
- Understanding of clinical workflows and electronic health record systems.
- Experience with medical imaging analysis or natural language processing for clinical text.
Work Authorization Requirement: This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the United States at the time of application and throughout the duration of employment. Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.