Description

As an Interdisciplinary System Engineer within Amazon Robotics, you will own the system design and discrete event modeling that drive critical deployment and design decisions at scale. You will leverage commercial simulation tools (AnyLogic, FlexSim, or equivalent) to model complex deployment processes, identify critical-path constraints, and recommend optimized sequencing strategies that reduce cycle time and cost across Amazon Robotics programs. You will also develop workcell operational models that quantify OEE (Overall Equipment Effectiveness) metrics sensitivity to hardware components and operational exceptions, enabling rapid, data-driven design iterations in early-stage development. You will be driving design decisions using the models you develop.

This role requires a unique blend of simulation expertise, systems engineering, and the ability to translate complex model outputs into actionable recommendations for cross-functional stakeholders including deployment teams, hardware engineers, and program leadership.

Key job responsibilities
- Own end-to-end discrete event simulation (DES) development using AnyLogic, FlexSim, or equivalent software to model deployment processes, workcell operations, and system-level workflows across Amazon Robotics programs.

- Identify critical path constraints through simulation analysis, providing data-driven recommendations to reduce deployment cycle time and cost while maintaining quality and safety standards.

- Develop optimized deployment sequencing strategies by modeling scenarios and trade-offs to inform resource allocation, task ordering, and contractor scheduling decisions.

- Build workcell operational models with OEE sensitivity analysis against hardware components, operational exceptions, and process variability.

- Conduct scenario analysis to project hardware design change impacts on OEE metrics, quantify uncertainty, and reduce costly physical prototyping cycles.

- Partner cross-functionally with deployment engineers, hardware design teams, manufacturing, operations, and program managers to validate model inputs and align outputs with real-world constraints.

- Communicate complex simulation results through clear visualizations, reports, and presentations for both technical and non-technical audiences.

- Establish best practices for simulation model development, validation, and version control.

- Contribute to system design reviews with simulation-informed insights on workcell layout, hardware integration, and process architecture. Apply systems engineering principles to analyze end-to-end manufacturing-to-installation dependencies.