Software Engineer - Simulation Fidelity
Anduril IndustriesSeattle, Washington, United StatesPosted 28 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 TRS Simulation team owns the ecosystem, frameworks, and guidance that make simulation possible, repeatable, and scalable across the Tactical Recon Strike business line. We don't just run sims, we define what it means for a simulation to be trustworthy . Our team operates across four pillars: Sim Infrastructure, Sim Fidelity, Sim Integrations, and Training Simulations, supporting products like Altius, Ghost, Bolt, and Anvil from early development through field deployment. Every fidelity improvement, every validated model, and every simulation environment we deliver directly determines whether autonomous systems are ready to fly real missions. Our vision is one simulation framework that serves every product and every deployment target, from a developer's laptop through CI pipelines, operator training environments, and large-scale HPC Monte Carlo campaigns. The same declarative workspace definition can be composed, extended, and deployed wherever simulation is needed, so teams spend their time on mission problems instead of reinventing infrastructure.
THE ROLE
This role is for someone who loves going deep on a problem. You'll identify where simulated components diverge from real-world behavior at the system level, work with our functional teams who own those subsystems to understand what a better model looks like, then own the integration, optimization, and validation within our simulation framework. The cycle is: analyze the gap, understand the domain, engineer the solution into the framework, and prove the fidelity improvement with data. The problems are genuinely complex, multi-physics, multi-rate, spanning both real-time and faster-than-real-time execution for large-scale Monte Carlo campaigns, and the feedback loop is measured in months, not years: your improvements are validated against real flight data and deployed to operational systems on a cadence that keeps pace with product development. You are expected to quickly develop working knowledge of the domains you touch (sensors, comms, navigation, environment, autonomy interfaces) and become an effective partner to our teams that own those subsystems. You'll care about performance characteristics, numerical stability, integration correctness, and building the validation tooling that makes fidelity measurable and repeatable. Whether your background is in industry or academia, what matters is demonstrated depth of ownership over complex software systems and the ability to pick up new domains and deliver reliable, performant software within them. You will own your solutions from design through delivery and long-term maintenance, with the support and collaboration of our team behind you. At the senior level, we expect you to operate across the full breadth of the simulation stack and help shape our team's technical direction.
WHAT YOU'LL DO
Analyze simulated subsystems within the framework to identify where system-level behavior diverges from real-world data, quantifying gaps and their downstream impact on simulation trustworthiness.
Partner with functional engineering teams (flight dynamics, perception, guidance, comms) who own subsystem models to understand requirements, integrate their higher-fidelity models into the simulation f ... (truncated, view full listing at source)
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