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Shield AI

Builds autonomous aircraft for defense

Staff Engineer - Autonomy Capabilities, Maritime

Robotics & Autonomous SystemsUpdated on Nov 14
Full-timeArlington County, Arlington, VA, USA

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a similar field, or equivalent practical experience.
  • Typically, at least 7 years of related experience with a bachelor's degree, 6 years with a master's degree, 4 years with a PhD, or equivalent work experience.
  • Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems.
  • Significant background in robotics technologies related to motion planning, behavior modeling, decision-making, or autonomous system design.
  • Significant experience with unmanned-system technologies and associated algorithms.
  • Experience with simulation tools and environments such as AFSIM or NGTS for testing and validation.
  • Ability to obtain a Secret clearance.
  • Ability to travel, typically around 25% of the year, to office locations, customer sites, and integration events.

Responsibilities

  • Create autonomy capabilities for unmanned surface vehicles, unmanned underwater vehicles, and cooperating unmanned aerial vehicles to perform single- and multi-agent missions beyond conventional motion planning and waypoint following.
  • Develop functionality that enables teams to search for, localize, and pursue targets while avoiding sensed threats and obstacles that pose risks to platform safety.
  • Lead the technical delivery of complex autonomy capabilities, help customers shape requirements, define technical approaches for the team, and drive technical execution throughout development.
  • Automate unmanned surface vehicle and/or unmanned underwater vehicle maneuvering through advanced motion planning while adhering to safety constraints, including keep-out volumes, cooperative and uncooperative vehicles, and depth limitations.
  • Define fusion modalities and sensor requirements, and develop observability-aware maneuvering capabilities to maximize information gathered from single- or multi-agent sensor networks for passive and active localization.
  • Keep vehicle safety central to autonomous behavior architectures by providing run-time assurance, ensuring COLREGS adherence, and building operator trust in mission autonomy.
  • Develop distributed optimization and task-allocation approaches for heterogeneous teaming to accomplish mission objectives using agents’ diverse capabilities.
  • Develop high-performance software modules that are well-tested, have clear interfaces and span of control, and are ready for mid-to-high Technology Readiness Level insertions.
  • Collaborate with perception, planning, simulation, hardware, and operational test teams to integrate autonomy solutions on real-world platforms.
  • Deploy autonomy capabilities to real surface vehicles; support integration and demonstration events; and analyze mission logs to verify software performance and validate operational effects.
  • Research and prototype new algorithms, identify tactical capability gaps, and propose solutions that advance autonomy roadmaps.

Desired Qualifications

  • Experience in multiple aerospace domains, such as air, land, sea, or space.
  • Experience across methodologies from classical control through optimization and applied machine learning or reinforcement learning.
  • Background in collaborative behaviors and swarm robotics.
  • Familiarity with domain-relevant Department of Defense or government programs.
  • Hands-on experience supporting integration events, customer demonstrations, or live exercises.

About the Company

Shield AI

Builds autonomous aircraft for defense

Shield AI builds autonomous aircraft and flight software for military and allied defense customers, with a focus on operations where conventional remote control breaks down. Its Hivemind AI pilot handles decisions during a mission, while the V-BAT aircraft gathers intelligence and locates targets. Aircraft makers use its software tools to develop and test their own autonomy, and its Aechelon business supplies visual and sensor simulation for pilot training. The company earns money from aircraft sales, autonomy software and contracted engineering and operational services. Shield AI was founded in 2015 and is headquartered in San Diego, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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