Amazon Industrial Robotics is seeking exceptional applied science talent to develop AI and machine learning systems that will enable the next generation of advanced manufacturing capabilities at unprecedented scale. We're building revolutionary software infrastructure that combines cutting-edge AI, large-scale optimization, and advanced manufacturing processes to create adaptive production control systems.

Identify and devise new scientific approaches for constraint identification, dispatch optimization, WIP release control, and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented

Lead the design, implementation, and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production

Design and build ML models and optimization algorithms including constraint prediction, starvation risk forecasting, and dispatch optimization

Write a significant portion of critical-path scientific code with solutions that are inventive, maintainable, scalable, and extensible

Execute rapid, rigorous experimentation with reproducible results, closing the gap between simulation and real manufacturing environments

Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone

Influence your team's science and business strategy through insightful contributions to roadmaps, goals, and priorities

Partner with manufacturing engineering, robotics simulation, and applied intelligence teams to ensure scientific approaches are grounded in operational reality

Drive your team's scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations

Actively participate in hiring and mentor other scientists, improving their skills and ability to deliver

Write clear narratives and documentation describing scientific solutions and design choices