Location: Houston, TX
Cap-Exempt H-1B Position — No lottery required
## **Summary** The department of Neurology at Baylor College of Medicine is looking for an experienced Artificial Intelligence Engineer II to support Dr. Ihab Hajjar. In this position, you will support the development and evaluation of machine learning and natural language processing systems for clinical research applications, with a focus on building reproducible data pipelines, analyzing multimodal data (e.g., speech and text), and contributing to model design, validation, and deployment. The role emphasizes collaboration with interdisciplinary teams and adherence to data governance and research standards while advancing methods relevant to AI engineering and research. ## **Job Duties** Machine Learning Systems & AI Engineering – 30% - Develop and maintain pipelines (Python-based) for data processing, feature extraction, and model evaluation. - Implement and test machine learning and NLP models, including training, fine-tuning, and benchmarking. - Conduct error analysis and iterative model improvement using structured experiments. - Build modular, reusable code to support reproducible experiments and configuration-driven workflows. Data Management, Quality Control, and Reproducibility -30% - Perform exploratory data analysis to assess data quality. - Implement validation checks, logging, and documentation to ensure data integrity and traceability. - Maintain structured datasets and features to support reproducible research workflows. - Support versioning and organization of data and model artifacts. Deployment, Inference, and Monitoring – 20% - Support model deployment in batch or research-oriented environments. - Implement and monitor inference workflows, including runtime performance and reliability. - Assist with maintaining pipelines as models or APIs evolve. - Contribute to improving efficiency, scalability, and robustness of model execution. Responsible AI, Security, and Compliance – 10% - Follow institutional policies for handling PHI and sensitive research