Oleria Security is focused on providing adaptive and autonomous identity security solutions. As an ML / AI Research Intern, you will lead a 12-week project to research, prototype, and validate a machine learning-driven access intelligence engine, aimed at improving access provisioning for organizations.
Responsibilities:
- You'll own this project end-to-end -- from research and data pipeline through working prototype and final presentation. Core work includes:
- ML research and prototyping
- Research, implement, and compare unsupervised learning approaches (e.g., k-means, hierarchical clustering, graph-based methods) to identify peer-group cohorts from employee attributes and entitlement data
- Generative AI integration
- Connect an LLM layer that translates ML outputs into human-readable cluster names and recommendation rationales that non-technical administrators can act on
- Synthetic data pipeline
- Design and generate realistic datasets with employee attributes, entitlement histories, and usage signals to support training, evaluation, and offline testing
- Extensible framework
- Build a modular, well-documented codebase designed to serve as the foundation for future access intelligence work beyond this internship
- Technical report
- Document your methodology, experiments, results, and recommendations in a written report that informs the production roadmap
- Final presentation
- Demo the working prototype and present key learnings to the engineering team and leadership