Software Sciences

AI & ML interests

Production AI infrastructure systems that solve real-world problems at scale. Designing hybrid cloud/on-prem AI platforms that balance cutting-edge capability with operational cost efficiency. Production MCP systems for cross-agent knowledge sharing. Workflow execution engines with parallel dependency management. Driven by the intersection of innovation and pragmatism: researching what's possible with transformer architectures and vector search, then architecting systems that deliver those capabilities reliably in production.

Team members 3