Senior Autonomy Engineer

We are seeking a Senior Autonomy Engineer to architect and deploy real-time multi-agent coordination, path planning, and collision avoidance systems for networked unmanned aerial swarms operating in noisy and contested environments.

Responsibilities:

Swarm Autonomy & Planning

• Design and implement distributed consensus algorithms and task allocation frameworks for agent swarms

• Develop robust path planning algorithms (RRT*, A*, optimization-based) that handle swarm formations, dynamic obstacles, no-fly and keep-in zones, and in-mission re-planning

• Develop optimized swarm search algorithms with decentralized decision making

• Build collision avoidance systems using geometric, optimization, and potential-field methods

• Create adaptive mission execution frameworks that respond to perception updates, communication dropouts, and adversarial conditions

• Design bandwidth-efficient coordination protocols that maintain swarm cohesion under severely constrained radio links

Real-Time Systems & Integration

• Implement autonomy stacks in ROS2 with C++ for deterministic performance on embedded compute

• Develop Simulink models for algorithm validation and hardware-in-the-loop testing

• Optimize computational performance to meet real-time constraints on resource-limited platforms

• Architect communication-aware planning strategies that balance information sharing with bandwidth limitations

Technical Leadership

• Define system architecture for networked collaborative autonomy with degraded communications

• Write technical specifications and design documents for autonomy capabilities

• Collaborate with perception, controls, radio systems, and flight test teams to integrate and validate solutions

Qualifications:

• Bachelor's in Computer Science, Robotics, Aerospace Engineering, Applied Mathematics, or related field (Master's preferred) – equivalent industry experience also welcome

• 5-7+ years of experience developing autonomous systems with focus on multi-agent coordination or motion planning

• Expert proficiency in C++ for real-time robotics/aerospace applications

• Strong hands-on experience with ROS2 architecture, nodes, and distributed systems

• Demonstrated expertise with Simulink for control and planning algorithm development

• Deep knowledge of path planning algorithms: sampling-based (RRT*, PRM), search-based (A*, D*), and optimization-based (MPC, trajectory optimization)

• Experience implementing collision avoidance and constraint satisfaction in multi-agent systems

• Solid understanding of distributed algorithms, consensus protocols, and network-aware planning

• Proven ability to integrate perception inputs (object tracks, maps, terrain) into planning decisions

• Experience designing systems for bandwidth-constrained or intermittent network communications

Preferred:

• Experience with swarm robotics, formation control, or multi-robot task allocation

• Knowledge of communication-constrained planning and decision-making under uncertainty

• Familiarity with radio communication protocols, message serialization, and data compression techniques

• Understanding of tactical data links, MAVLink, or other UAV communication standards

• Background in networked control systems or event-triggered communication strategies

• Familiarity with aerial platform dynamics and UAV autopilots (PX4, ArduPilot)

• Background in optimal control, game theory, or distributed optimization

• Experience with GNSS-denied navigation or contested environment operations

• Experience in motion planning, multi-agent systems, or autonomous systems

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