- – Design and own distributed architecture for DGGS as a referencing layer.
- – Drive end-to-end system design decisions with full accountability for tradeoffs.
- – Build spatial indexing infrastructure for real-time, cross-scale data access.
- – Lead system architecture and implementation for scalable, secure services.
- – Design and operate AI-driven multi-model orchestration pipelines for workflows.
- – Build automated test harnesses to ensure code quality and prevent regressions.
- – Design and optimize ML models for accurate health data extraction and processing.
- – Apply reinforcement learning techniques to enhance data collection and model accuracy.
- – Collaborate with cross-functional teams to develop client-focused machine learning solutions.