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Salary: USD 129,000 - 171,000 / annual
Anduril Industries is a defense technology company transforming U.S. and allied military capabilities through advanced technology. The Battlespace Awareness Command and Control Software team solves complex, real-world problems using cutting-edge algorithms and intelligent software integrations, with a focus on delivering mission-critical deployed solutions.
You will join a small, collaborative team within the Command and Control Software organization, contributing hands-on expertise in path planning and route optimization. Your responsibilities will include:
- Prototyping and deploying state-of-the-art algorithms for global and local path planning, trajectory optimization, and multi-agent coordination within command and control systems
- Developing online (real-time) path planning capabilities that replan safely and efficiently as mission conditions, threats, and vehicle states change
- Designing and developing high-performance software for real-time C2 systems deployed on operational platforms, from operator-facing mission planning tools to autonomous tasking and routing services that orchestrate fleets of unmanned systems
- Implementing robust planners, search algorithms, and decision-making systems that generate safe, feasible, and optimal routes in dynamic, uncertain, and contested environments
- Analyzing system performance using high-fidelity simulations, modeling tools, and statistical techniques to validate planner behavior across diverse mission scenarios
- Supporting customer success by developing algorithms and software for mission-critical use cases, including collaborative autonomy, asset routing, and obstacle and threat avoidance
- Integrating path planning technologies into the broader command and control software stack and development lifecycle
- Translating technical progress into clear, actionable insights for diverse stakeholders, including colleagues, operators, and end-users
REQUIREMENTS:
- 3+ years of experience in algorithm design, software development, and mathematical modeling with programming expertise in C/C++ and/or Rust
- Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling-based planners (RRT, RRT*, PRM), and online/real-time replanning approaches
- Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization and trajectory prediction; and/or development of predictive models for vehicle dynamics and weapon system effectiveness (e.g., 6-DoF simulation, intercept analysis)
- Solid understanding of applied mathematics, including linear algebra, optimization, computational geometry, and graph theory
- Knowledge of vehicle dynamics, kinematic constraints, and control theory as applied to autonomous ground, air, or maritime platforms tasked through C2 systems, including high-speed aerial vehicles
- Familiarity with map representations, terrain reasoning, state estimation, and efficient handling of large-scale geospatial and environmental data within distributed C2 architectures
- Exposure to machine learning as applied to planning and decision-making, including reinforcement learning, learned heuristics, and behavior prediction
- Ability to write robust, concurrent code for planning under uncertainty and operation in complex, dynamic, contested environments
- Demonstrated ability to work across development lifecycles, from prototyping to optimizing production systems
- Eligible to obtain and maintain an active U.S. Secret security clearance
NICE TO HAVE:
- Experience with Rust for high-performance, safety-critical software
- Exposure to mixed greenfield/brownfield codebases, including extending an existing planning/routing stack in production
