Rice University is seeking a Machine Learning Engineer to drive analytics that underpin its Momentous strategic initiatives, including fundraising innovation, operational efficiency, and research enablement.
Requirements
- Python, SQL, statistics, ML; plus deep expertise in at least two areas: advanced ensembling and sampling techniques, forecasting, NLP/LLMs, transfer learning, or MLOps
- Tools: scikit-learn, statsmodels, TensorFlow/PyTorch, Git
- Apply advanced analytics—clustering, time-series forecasting, NLP/LLMs—with Python, TensorFlow/PyTorch, and Hugging Face
- Exceptional analytical and problem-solving skills, with a deep understanding of advanced statistical analysis and machine learning
- Demonstrated experience deploying AI/ML systems into production
- Comfortable wearing many hats—ranging from architecting end-to-end workflows to collaborating with domain experts, building pipelines, and leading training sessions for non-technical users
- Proven track record of continuous learning and curiosity, as well as the ability to quickly adapt to emerging tools, methods, and challenges
Responsibilities
- Execute the ML lifecycle: data ingestion, feature engineering, modeling, validation, deployment, and monitoring
- Architect and implement CI/CD pipelines and containerized deployments (Git, Docker, etc.)
- Translate complex functional, technical, and business requirements into architectural designs
- Develop high-level application designs and direct detailed design work of developers
- Develop proofs-of-concept and prototypes to validate and compare design alternatives
- Develop reference architectures, coding samples, and quality assurance (QA) strategies
- Recommend strategies for system monitoring, performance improvements, and capacity planning
Other
- Bachelor’s degree
- 4 years of experience as a Data Scientist or Machine Learning Engineer
- In lieu of the experience requirement, additional related education above and beyond what is required may be substituted on an equivalent year-for-year basis
- Master’s degree (preferred)
- Degree in a quantitative field (preferred)
