 Contribute to a production-level AI memory system, MemMachine, that improves contextual retrieval across long documents

and large-scale inference tasks by 30%.

 Build and maintain hybrid cache synchronization and persistence layers, reducing model latency by 25% and improving

throughput on distributed GPUs.

 Benchmark and optimize token recall efficiency, achieving 30% faster sequence reconstruction in evaluation pipelines.

 Resolve 12+ GitHub issues addressing caching, model alignment, and inference stability, and improve scalability through

collaborative PRs and AWS deployment automation.

We are building Foundly, a centralized AI powered SaaS platform that modernizes how organizations manage and recover lost property. The platform is designed for institutional scale, built on a recurring revenue model, and targeting $4M+ across seed funding and ARR by 2027, positioning Foundly as a leading solution in this market.

Supervise daily operations at the University of Rochester River Campus Libraries service point, managing workflows across service desks and student teams. Train and mentor student assistants, oversee information systems for accuracy, and support IT service and database management to enhance the experience for students and faculty.