Software Engineer - Simulation Fidelity

Anduril Anduril · Defense · Seattle, WA · Tactical Recon & Strike

Software Engineer focused on improving the fidelity of simulation environments for defense autonomous systems. This involves analyzing discrepancies between simulated and real-world behavior, integrating higher-fidelity models, optimizing performance, and building validation tooling against real flight data. The role requires strong software engineering skills in systems and scripting languages, comfort with numerical computing, and end-to-end ownership of complex software systems.

What you'd actually do

  1. 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.
  2. 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 framework, and validate the integration through statistical analysis.
  3. Engineer framework-level solutions that enable higher-fidelity models to run efficiently, addressing performance constraints, timing coordination, and numerical integration concerns.
  4. Build and maintain validation tooling and benchmarks that make fidelity measurable: automated comparison against real-world data, regression detection, and acceptance threshold enforcement.
  5. Design and run Monte Carlo validation campaigns to verify that fidelity improvements hold across parameter sweeps and edge cases, not just nominal conditions.

Skills

Required

  • Bachelor's degree in Computer Science, Engineering, Physics, Mathematics, or a related field.
  • At least 3+ years of professional software engineering experience with a systems language (C++, Rust) and an analysis/scripting language (Python, MATLAB).
  • Experience with performance analysis and optimization of complex software systems (profiling, bottleneck identification, latency reduction, computational efficiency).
  • Comfort with numerical and scientific computing concepts (integration methods, statistical analysis).
  • Demonstrated ability to take deep ownership of a system end-to-end: understand it, identify problems, design solutions, implement them, and validate the results with data.
  • Experience building or maintaining automated test/validation infrastructure that enforces cor

What the JD emphasized

  • own the integration, optimization, and validation within our simulation framework
  • own your solutions from design through delivery and long-term maintenance
  • demonstrated depth of ownership over complex software systems
  • take deep ownership of a system end-to-end
  • automated test/validation infrastructure that enforces cor