Senior Software Engineer - Guidance, Navigation, and Control

Anduril Anduril · Defense · Huntsville, AL · Mission Systems : Battlespace Awareness Engineering

Senior Software Engineer focused on Guidance, Navigation, and Control (GNC) for defense technology, specifically developing and deploying algorithms for path planning, route optimization, and multi-agent coordination within command and control systems for autonomous platforms. The role involves designing robust planners and decision-making systems, integrating them into real-time C2 software, and analyzing performance using simulations and statistical techniques. Machine learning, including reinforcement learning, is applied to planning and decision-making under uncertainty in dynamic, contested environments.

What you'd actually do

  1. Prototype and deploy state-of-the-art algorithms for global and local path planning, trajectory optimization, and multi-agent coordination within command and control systems.
  2. Develop high-performance software for real-time C2 systems, ranging from operator-facing mission planning tools to autonomous tasking and routing services that orchestrate fleets of unmanned platforms.
  3. Design and implement robust planners, search algorithms, and decision-making systems that generate safe, feasible, and optimal routes in dynamic, uncertain, and contested environments.
  4. Analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate planner behavior across diverse mission scenarios.
  5. Drive customer success by customizing algorithms and software for mission-critical use cases, including collaborative autonomy, asset routing, and obstacle and threat avoidance.

Skills

Required

  • algorithm design
  • software development
  • mathematical modeling
  • C/C++
  • Python
  • Matlab
  • path planning techniques (A*, D* Lite, RRT, RRT*, PRM, lattice/grid-based)
  • guidance, navigation, and control (GNC)
  • trajectory optimization
  • predictive models for vehicle dynamics
  • applied mathematics (linear algebra, optimization, computational geometry, graph theory)
  • vehicle dynamics
  • kinematic constraints
  • control theory
  • map representations
  • terrain reasoning
  • handling large-scale geospatial and environmental data
  • machine learning for planning and decision-making
  • reinforcement learning
  • learned heuristics
  • behavior prediction
  • robust systems for planning under uncertainty
  • multi-agent coordination
  • operation in complex, dynamic, contested environments
  • work across development lifecycles (prototyping to production optimization)

Nice to have

  • 6-DoF simulation
  • intercept analysis
  • autonomous ground, air, or maritime platforms
  • distributed C2 architectures
  • collaborative autonomy
  • asset routing
  • obstacle and threat avoidance

What the JD emphasized

  • U.S. Top Secret security clearance
  • machine learning as applied to planning and decision-making
  • reinforcement learning
  • learned heuristics
  • behavior prediction
  • planning under uncertainty
  • multi-agent coordination
  • operation in complex, dynamic, contested environments

Other signals

  • AI-powered operating system
  • cutting-edge autonomy, AI, computer vision, sensor fusion
  • real-time, 3D command and control center
  • autonomous mission execution
  • path planning, route optimization
  • multi-agent coordination
  • autonomous tasking and routing services
  • orchestrate fleets of unmanned platforms
  • planners, search algorithms, and decision-making systems
  • planning under uncertainty
  • multi-agent coordination
  • collaborative autonomy
  • asset routing
  • obstacle and threat avoidance
  • machine learning as applied to planning and decision-making
  • reinforcement learning
  • learned heuristics
  • behavior prediction