Sr. Simulation Engineer, Paint​/GA

About Rivian

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions‑free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.

As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

The Factory Design & Simulation team is at the core of Rivian's mission to redefine the future of automotive manufacturing. By turning industrial strategy into optimized value streams we enable production of market‑leading EVs  part of Digital Manufacturing Engineering & Automation we create standardized tools and processes for throughput and material flow simulations. By understanding high‑level factory goals and collaborating with teams designing individual systems, our team ensures the holistic factory design meets Rivian’s ambitious objectives.

In this highly collaborative role, you will use discrete event simulation (DES) to guide factory design from early concepts to full operation. Partnering with industrial strategy, vertical, and integration teams, you'll define throughput architecture, establish buffer requirements, and create DES standards to ensure system designs achieve required production rates. Your responsibilities extend from executing simulations throughout the design process to identifying bottlenecks during production ramp‑up and validation against actual production.

This position requires a comprehensive grasp of Manufacturing Engineering principles, complemented by a strong proficiency in simulation modeling. We seek candidates who solve complex problems using a first‑principles approach and possess an intrinsic drive for design optimization. The successful candidate will thrive in a fast‑paced environment, contributing to an agile, highly motivated team. You should be meticulous, analytical, and collaborative, with the ability to think at a systems level about ambiguous challenges and apply logical reasoning to build models that guide optimal factory design outcomes.

Join us in our mission to Keep the World Adventurous Forever.

This position is located at our Normal, IL or Stanton Springs North, GA facility and relocation is mandatory. The role will directly report to a Manager, Manufacturing Engineering.

• Build discrete event simulation models for various parts of the manufacturing or logistic process – Body, Paint, Drive Unit, Battery, and General Assembly, Supply Chain
• Manage multiple integrators and integrate their deliverables into shop and factory models
• Develop decision making frameworks with quantifiable tradeoffs for the entire factory or individual manufacturing processes
• Optimize plant layouts by analyzing throughput capabilities, bottlenecks, buffer sizing, and material routing
• Collaborate with the Automation & Controls team to collect and subsequently incorporate real‑world data to validate models and suggest improvements
• Develop and sustain digital twin models to effectively test and validate the designs of manufacturing systems.
• Co‑develop standards for discrete event simulation models incl. development of a library of simulation assets with properties and performance characteristics.

• Bachelor’s degree in Industrial Engineering, Mechanical/Manufacturing Engineering, or Computer Science
• 5+ years of experience in industrial or manufacturing engineering, with focus on applying discrete event simulation to enhance process efficiency.
• Extremely proficient with discrete‑event simulation tools
• Familiarity with creating new features and modules within discrete event simulation platforms using FlexScript, Simtalk, C++, and/or Python.
• Knowledge of statistics, uncertainty, and sensitivity analysis
• Strong analytical and organizational skills and ability to manage several projects at the same time in a highly variable and uncertain environment
• A track record of quantitatively resolving ambiguous, systems‑level problems.
• Effective…