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Shield AI

Builds autonomous aircraft for defense

Senior Staff Engineer - Autonomy Capabilities, Maritime

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeWashington, DC, USA

About the Job

Requirements

  • A minimum of 10 years of related experience with a Bachelor’s degree, 9 years with a Master’s degree, 7 years with a PhD, or equivalent work experience is typically required.
  • 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 accompanying algorithms, ideally in the space domain.
  • Experience with simulation tools and environments such as AFSIM and NGTS for testing and validation.
  • Ability to troubleshoot and optimize system performance.
  • Ability to work effectively in a collaborative, multidisciplinary environment.
  • Ability to obtain a Secret clearance.

Responsibilities

  • Create autonomy capabilities for unmanned surface vehicles, unmanned underwater vehicles, and cooperating unmanned aerial vehicles, enabling advanced single- and multi-agent teaming missions.
  • Develop autonomy 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 direction for the portfolio and drive the evolution of autonomy capabilities and architectures across multiple programs.
  • Decompose ambiguous customer needs into tangible design approaches and mentor engineers across the organization.
  • Automate unmanned surface vehicle and/or unmanned underwater vehicle maneuvering through advanced motion planning and adherence to safety constraints, including keep-out volumes, cooperative and uncooperative vehicles, and depth limitations.
  • Employ 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 within autonomous behavior architectures by providing run-time assurance, ensuring COLREGS adherence, and building operator trust in advanced mission autonomy.
  • Develop distributed optimization and task-allocation approaches for heterogeneous teaming to accomplish mission objectives by utilizing agents’ diverse capabilities for the overall team’s advantage.
  • 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 system operational effect.
  • Contribute to autonomy roadmaps by researching and prototyping algorithms, identifying tactical capability gaps, and proposing novel solutions.
  • Travel around 25% of the year to office locations, customer sites, and flight integration events.

Desired Qualifications

  • Experience in multiple aerospace domains, such as air, land, sea, and space.
  • Experience across methodologies from classical control through optimization and applied machine learning/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, and/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
Series H
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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