- Own the ML and optimization roadmap for Dispatch OS, deciding which problems use ML, solvers, or heuristics.
- Design end-to-end architecture for model serving, evaluation, and optimization.
- Lead ambiguous, high-stakes modeling and optimization problems from framing through production.
- Set standards for experimentation, evaluation, and production ML, and mentor engineers through design reviews, pairing, and code review.
- Partner with Product and leadership on product strategy and opportunities for ML and operations research.
- Design and ship quote selection, dynamic pricing, and reliability-scoring models.
- Build demand and volume forecasting models to help plan driver and fleet capacity.
- Develop solver-based optimization for batching, route optimization, and vehicle or fleet recommendations.
- Apply LLMs and AI agents to dispatch workflows, including document extraction, quote follow-ups, and exception handling.
- Build evaluation frameworks and automated pipelines for model training, deployment, and monitoring.
Machine LearningMLOps