Optimization AI
Hierarchical multi-agent system with domain-constrained specialist delegation for cross-vertical optimization. Orchestrator-mediated coordination across regulatory compliance, demand forecasting, and inventory agents.
Hierarchical multi-agent system for cross-vertical optimization across 2 industry verticals. Enforces domain-specific constraints at the agent level and evaluates optimization quality with statistical rigor.
Optimization across complex, interdependent decision spaces requires coordinating procurement, inventory, logistics, and compliance with constraints varying by vertical.
Hierarchical delegation. Domain-specific constraints enforced at the specialist level. The orchestrator resolves inter-agent conflicts through evidence weighting.
Rashanjot Kaur - AI Engineer
Building ML pipeline with statistical validation.
6 open role(s)
Applied AI Engineer - Open
Extend specialist agents, orchestration, and constraint-aware optimization flows across verticals.
Apply →Backend Engineer - Open
Design orchestration layer, agent coordination APIs, and integration with validation pipelines.
Apply →Frontend Engineer - Open
Build Streamlit/Plotly interfaces for optimization dashboards, scenarios, and statistical summaries.
Apply →Data Engineer - Open
Ingest and normalize supply-chain datasets; feature pipelines for forecasting, inventory, and validation.
Apply →AI Researcher - Open
Statistical validation, ablation studies, and research documentation for hierarchical multi-agent optimization.
Apply →DevOps / MLOps - Open
Reproducible experiment runs, deployment for Streamlit and Python services, monitoring for batch workflows.
Apply →