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Shield AI

Builds autonomous aircraft for defense

Senior Software Engineer - Autonomy Capabilities, Maritime

Robotics & Autonomous SystemsUpdated on Nov 14
Full-timeBoston, MA, 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 10 years of related experience with a bachelor's degree, 9 years with a master's degree, or 7 years with a PhD, or equivalent work experience.
  • Proficiency in programming languages such as C++ and Python.
  • Significant background in one or more robotics technology areas related to control systems, motion planning, optimization, tactical behaviors, or distributed decision-making.
  • Significant experience with unmanned system technologies and associated algorithms, ideally in the maritime domain.
  • Experience with simulation tools and environments such as AFSIM, NGTS, or similar for testing and validation.
  • Ability to obtain a Secret clearance or higher.

Responsibilities

  • Develop autonomy capabilities for unmanned surface vehicles, unmanned underwater vehicles, and cooperating unmanned aerial vehicles to support advanced single- and multi-agent missions beyond conventional motion planning and waypoint following.
  • Build functionality that enables teams to use diverse payloads and maneuvering characteristics to search for, localize, and pursue targets while avoiding sensed threats and obstacles.
  • Develop and own major features end-to-end, from design through operational deployment, working with cross-functional teammates to achieve program goals.
  • 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.
  • Use passive and active localization approaches by defining fusion modalities, sensor requirements, and observability-aware maneuvering capabilities to maximize information from single- or multi-agent sensor networks.
  • 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 achieve 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.
  • Contribute to autonomy roadmaps by researching and prototyping algorithms, identifying tactical capability gaps, and proposing solutions.
  • Mentor junior engineers and, in limited capacities, interface with customers.
  • Travel approximately 25% of the year to office locations, customer sites, and integration events.

Desired Qualifications

  • Experience across multiple domains, such as air, land, sea, or space.
  • Experience with methodologies ranging 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.
  • Experience in applied research and development.

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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