Principal Ai/ml Software Engineer - Autonomy (onsite)

RTX RTX · Aerospace · cedar rapids, IA +1 · Engineering

Principal AI/ML Software Engineer focused on designing and implementing distributed reasoning, multi-agent coordination, and mission-adaptive autonomy technologies for defense applications. The role involves architecting intelligent, resilient, edge-deployed AI systems and transitioning advanced autonomy concepts into operational prototypes.

What you'd actually do

  1. Develop multi‑agent coordination algorithms and distributed C2 autonomy behaviors
  2. Apply reinforcement learning to resource allocation, tasking, and cooperative/adversarial scenarios
  3. Design intent‑driven autonomy functions that translate commander intent into executable behaviors
  4. Implement multimodal human‑machine interaction capabilities and operator‑centric mission tools
  5. Engineer probabilistic reasoning, adaptive learning, and intelligent data‑management components for DDIL environments

Skills

Required

  • Python
  • C++
  • Rust
  • Go
  • PyTorch
  • TensorFlow
  • ROS/ROS2
  • probabilistic reasoning
  • reinforcement learning
  • multi-agent systems
  • distributed computing
  • edge-deployed systems
  • MLOps
  • simulation-based testing
  • mission analytics

Nice to have

  • explainable AI
  • safety-constrained autonomy
  • guardrails
  • human-machine teaming
  • contested environments
  • bandwidth-limited environments
  • Neurosymbolic AI
  • distributed Bayesian inference
  • multi-agent coordination
  • distributed optimization
  • Value-of-Information-driven algorithms
  • edge-to-cloud distributed autonomy architectures
  • advanced research programs
  • IRAD strategy
  • technology transition planning

What the JD emphasized

  • U.S. citizenship is required
  • ability to obtain and maintain a U.S. government issued security clearance is required
  • Active and existing security clearance required after day 1

Other signals

  • multi-agent coordination
  • distributed reasoning
  • reinforcement learning
  • edge-deployed AI systems
  • operational prototypes