Defense Autonomy Engineer

Applied Intuition Applied Intuition · Robotics · Ann Arbor, MI · Government

Develops collaborative autonomy behaviors for heterogeneous autonomous vehicles across different domains and sensor suites to accomplish complex missions. Designs and develops multi-agent multi-domain behavioral autonomy algorithms, integrates tactical autonomy solutions, deploys containerized solutions, and troubleshoots complex issues.

What you'd actually do

  1. Adapt and develop cutting edge, modular, and agile autonomy capabilities in the fields of optimization, persistent search, and coordinated behaviors, applicable to a diverse set of Defense problems
  2. Integrate tactical autonomy solutions onto hardware platforms, interface sensors, and test and validate autonomous behaviors, including on-site demonstrations for software field testing and evaluation exercises with the defense customers
  3. Design, test, and ultimately implement software within a component-based architecture, including occasionally integrating externally developed software capabilities into the system
  4. Deploy containerized autonomy solutions to embedded Linux devices, leveraging computer-in-the-loop testing and profiling, and efficiently collecting performance data
  5. Troubleshoot and debug complex issues related to behavioral autonomy and system performance, ensuring robust and reliable operation

Skills

Required

  • MS or PhD in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or equivalent OR 2+ years of relevant experience designing multi-agent autonomy
  • Understanding of Multi-Agent Algorithms including Ant-Colony Optimization, Swarm Particle Optimization, Stigmergy, and Wolf Pack Algorithm
  • Experience with Swarm or Multi-agent Systems and Optimization
  • Deep understanding of behavior logic frameworks (state machines, behavior trees, hierarchical task networks)
  • Modern C++ development (2011, 2017, 2020, smart pointers, etc.)
  • CMAKE
  • Python
  • Bash
  • U.S. Citizenship
  • Eligibility for U.S. security clearance

Nice to have

  • Passion for solving complex problems with little supervision in a fast-paced environment
  • Ability to balance multiple priorities in a fast-paced, highly collaborative, frequently changing, and sometimes ambiguous environment
  • Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate across multiple teams
  • Interdisciplinary background, with evidence of continual learning
  • Current U.S. SECRET security clearance

What the JD emphasized

  • MS or PhD in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or equivalent OR 2+ years of relevant experience designing multi-agent autonomy
  • Understanding of Multi-Agent Algorithms including Ant-Colony Optimization, Swarm Particle Optimization, Stigmergy, and Wolf Pack Algorithm
  • Experience with Swarm or Multi-agent Systems and Optimization
  • Deep understanding of behavior logic frameworks (state machines, behavior trees, hierarchical task networks)
  • Must be a U.S. Citizen
  • Must hold or be eligible to obtain and maintain a U.S. security clearance

Other signals

  • multi-agent autonomy
  • heterogeneous autonomous vehicles
  • complex mission vignettes
  • behavioral autonomy algorithms