Rice University is seeking a development engineer to build and maintain machine learning (ML) software and pipelines to power digital health innovations.
Requirements
- Strong programming skills in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Familiarity with version control (Git) and collaborative development
- Experience with data pipelines (e.g., Airflow, Prefect, Luigi) and cloud platforms (e.g., AWS, GCP, or Azure)
- Understanding of CI/CD workflows, containerization (e.g., Docker, Kubernetes)
- Experience deploying ML in clinical/research settings
- Background in signal processing, time-series, or imaging data
Responsibilities
- Design, build, and maintain end-to-end ML pipelines for data ingestion, preprocessing, training, validation, and deployment
- Collaborate with data scientists, clinicians, and engineers to translate research models into scalable production systems
- Develop APIs, microservices, and cloud-based deployment frameworks to support ML applications
- Ensure reproducibility, scalability, and compliance with healthcare data standards (HIPAA, FDA guidance)
- Optimize pipelines for performance, cost, and reliability
- Contribute to code reviews, documentation, and team best practices
Other
- 2+ years of related experience
- On-campus position: This position is exclusively on-site, necessitating all duties to be performed in person.
- Continued employment is contingent on the renewal of funding.
- Experience in digital health, medical data, or regulated environments
- Knowledge of healthcare data formats (HL7, FHIR, DICOM)
