Industrial Engineer, Production Controls & Simulation

Anduril Industries
Costa Mesa, California, United StatesPosted 15 April 2026

Job Description

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. ABOUT THE TEAM Anduril's Manufacturing Technology, Maritime Team is building the next generation of advanced AI-driven factories to manufacture large-scale autonomous maritime systems at unprecedented speed and scale. The Maritime Manufacturing Technology Team is responsible for rapidly developing and implementing manufacturing technologies and processes for cutting-edge defense hardware, including deployable static and moving surface, undersea and sea to air vehicles, and scaling these products in our new manufacturing facilities. Our industrialization approach combines advanced manufacturing methods, digital integration, and adaptive planning to compress development timelines while de-risking production decisions. ABOUT THE JOB As an Industrial Engineer on the Production Control team, you will develop and maintain discrete event simulation models and critical chain schedules that drive production planning for Anduril's advanced AI factory. You will use simulation and modeling tools to visualize production systems, identify bottlenecks, and optimize resource allocation—translating analytical insights into actionable production control decisions. You will also integrate technology into daily workflows by writing scripts and building automated processes that increase the team's throughput and decision speed. This is a hands-on role for someone with strong Operations Research fundamentals who is eager to apply simulation, optimization, and scripting to real manufacturing problems at scale. WHAT YOU’LL DO Develop and maintain discrete event simulation (DES) models of maritime manufacturing processes to support production planning and facility layout decisions Build and operate critical chain project management models to drive production scheduling and resource leveling Write scripts and build technology-driven workflows to automate production control tasks and streamline planning processes Collaborate with manufacturing technology teams to validate simulation assumptions against physical reality and implement process improvements Provide data-driven analysis to support capital equipment investments, make-vs-buy decisions, and capacity planning Create visualizations and reports that enable cross-functional teams (design, ops, finance, leadership) to understand factory behavior and make informed decisions Identify production bottlenecks, resource conflicts, and capacity constraints before they become expensive problems REQUIRED QUALIFICATIONS Bachelor's degree in Industrial Engineering, Operations Research, Manufacturing Engineering, Systems Engineering, or related technical field 2+ years of experience in simulation modeling, production planning, or industrial engineering Foundational knowledge of discrete event simulation concepts and at least one DES platform (FlexSim, Simio, AnyLogic, Arena, or equivalent) Strong analytical skills with the ability to translate complex data into actionable insights Willingness to integrate new technology into workflows — writing scripts, automating processes, and adopting tools that accelerate the team Proficiency in data analysis and visualization tools (Python, Excel, or similar) Ability to work directly with manufacturing teams to implement process improvements b ... (truncated, view full listing at source)
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