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Salary: USD 191,000 - 253,000 / 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 real-world deployed impact rather than academic research.
In this role, you will define and influence the direction of a small team within the Command and Control Software organization, leveraging deep subject-matter expertise in path planning and route optimization. You will 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. Your work will span high-performance software development for real-time C2 systems, from operator-facing mission planning tools to autonomous tasking and routing services that orchestrate fleets of unmanned platforms.
Key responsibilities include designing and implementing robust planners, search algorithms, and decision-making systems that generate safe, feasible, and optimal routes in dynamic, uncertain, and contested environments. You will analyze system performance using high-fidelity simulations, innovative modeling tools, and rigorous statistical techniques to validate planner behavior across diverse mission scenarios. You will drive customer success by customizing algorithms and software for mission-critical use cases, including collaborative autonomy, asset routing, and obstacle and threat avoidance. Integration of path planning technologies into the broader command and control software stack is critical, spanning from requirements definition through testing and optimization. Finally, you will translate technical progress into clear, actionable insights for diverse stakeholders, including colleagues, operators, and end-users.
REQUIREMENTS:
- 8+ years of experience in algorithm design, software development, and mathematical modeling with programming expertise in C/C++, Python, and Matlab
- Strong knowledge of path planning techniques, such as graph-based search (A*, D* Lite), sampling-based planners (RRT, RRT*, PRM), and lattice or grid-based planners
- Demonstrated experience in guidance, navigation, and control (GNC); trajectory optimization; 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
- Familiarity with map representations, terrain reasoning, and efficient handling of large-scale geospatial and environmental data within distributed C2 architectures
- Background in machine learning as applied to planning and decision-making, including reinforcement learning, learned heuristics, and behavior prediction
- Ability to engineer robust systems for planning under uncertainty, multi-agent coordination, 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. Top Secret security clearance
- Academic transcripts required as part of early application process to assess technical and analytical abilities; unofficial transcripts acceptable with option to redact non-technical information
