Mission Autonomy Lead

Anduril Industries

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Costa Mesa, CA
Salary
$190,000–$250,000 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $186k
This role $220k
$131k most similar roles pay here $263k

This role pays more than 77% of similar roles. Most pay $157,600–$214,187 — the shaded band above. At the midpoint, this role pays about $220k versus about $186k for comparable roles.

Based on 239 similar postings.

Employer

About Anduril Industries

Anduril Industries is a defense technology company that builds advanced hardware and software systems for national security, including autonomous drones, surveillance systems, and the Lattice AI command platform.

Anduril Industries currently has 1836 open roles on FindRole.

Listed pay typically runs $146,000–$194,000 across 1620 roles with salary data.

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At a glance

TL;DR · Mission Autonomy Lead

As the Mission Autonomy Lead on the Maneuver Dominance team, you will own the autonomy software stack for a maritime autonomous vehicle. You will be responsible for the entire lifecycle of mission execution, including system design, planning, perception, debriefing, and developing the underlying software infrastructure such as CI/CD and simulation environments. The role involves defining how vehicles navigate and learn across long ranges of open ocean while managing requirements through MBSE artifacts. To succeed, you must possess expertise in C++, Python, Linux-based real-time operating systems, and tools like Git or Jenkins. You will also leverage knowledge of ROS/ROS2, computer vision, and modular architecture standards like MOSA to solve complex problems involving autonomous aviation operations in contested environments. This role requires a blend of technical leadership and experience with high-assurance software for mission-critical maritime applications.

What you'll do

  • Own the autonomy software architecture including planning, execution, perception, and debriefing systems.
  • Drive the design of mission planning systems for autonomous aviation operations.
  • Develop mission execution software to manage vehicle behavior during active missions.
  • Build and maintain software development infrastructure including CI/CD pipelines and SITL/HITL simulations.
  • Define interfaces between the autonomy stack and vehicle management systems using MOSA principles.
  • Manage autonomy deliverables across development phases using MBSE artifacts and requirements traceability.
  • Develop test and simulation fixtures to validate autonomous capabilities.
  • Provide technical mentorship to software and systems engineers within the team.

What we're looking for

  • Bachelor's degree in Computer Science, Robotics, Aerospace Engineering, or equivalent.
  • 5+ years of experience in autonomous systems, robotics, or AI/ML.
  • Experience delivering software through full product development cycles.
  • Demonstrated experience with autonomous navigation, planning, or perception systems.
  • Experience with modeling, simulation, and SITL/HITL testing.
  • Experience developing safety-critical or high-assurance software.
  • Proficiency in C++ and/or Python for real-time and mission-critical software systems.
  • Experience with Linux-based embedded or real-time operating systems.
  • Experience with version control and CI/CD tooling such as Git, Jenkins, or GitLab CI.
  • Ability to obtain and maintain a U.S. Secret security clearance.
  • Experience with autonomous aviation systems (preferred).
  • Working knowledge of ROS/ROS2, behavior trees, or mission planning frameworks (preferred).
  • Experience with computer vision, EO/IR sensor processing, or airborne perception (preferred).
  • Familiarity with distributed software architectures and edge computing (preferred).
  • Experience designing to open systems architecture standards like MOSA/WOSA for defense acquisition (preferred).
  • Familiarity with MBSE tooling and digital engineering practices such as SysML or Cameo (preferred).
  • Familiarity with containerization and deployment tools like Docker or Kubernetes (preferred).
  • Experience with simulation environments relevant to aviation, such as Gazebo or JSBSim (preferred).
  • Experience with real-time middleware/pub-sub frameworks like DDS or ZeroMQ (preferred).
  • Familiarity with cross-compilation for embedded hardware like NVIDIA Jetson (preferred).
  • Experience with static analysis, formal verification, or certification-adjacent tooling (preferred).

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