Research Engineer

• Define and build the intelligence at the core of Dispatch OS, Burq's platform for ML-assisted dispatch decisions
• Set technical direction for how Burq prices, selects, forecasts, and routes deliveries
• Personally build high-leverage models and optimization systems
• Own the ML and optimization roadmap and make key technical bets
• Design end-to-end architecture for model serving, evaluation, and optimization at scale
• Lead ambiguous, high-stakes modeling and optimization problems from framing through production
• Guide technical work across Engineering and Data
• Set standards for experimentation, evaluation, and production ML
• Mentor engineers through design reviews, pairing, and code review
• Partner with Product and leadership on product strategy and ML/OR competitive advantage
• Design and ship quote-selection, dynamic-pricing, and reliability-scoring models
• Build demand and volume forecasting models
• Develop solver-based optimization for batching, route optimization, and vehicle/fleet recommendation
• Apply LLMs and AI agents to dispatch workflows, including provider-rule extraction and quote follow-ups
• Build replayable evaluation frameworks for customer model validation
• Translate operational constraints into model requirements, scoring logic, and optimization formulations
• Design and own automated MLOps pipelines for training, deployment, monitoring, and retraining
• Use AI tools daily to accelerate experimentation, evaluation, and debugging

Explore Staff Machine Learning, Operations Research Engineer at Burq. Review requirements and application details.