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Shield AI

Builds autonomous aircraft for defense

Discrete Planning Engineer

Robotics & Autonomous SystemsUpdated on Nov 11
Full-time

About the Job

Requirements

  • Typically requires a PhD with graduate work in Optimization or Operations Research, or a Master's degree with at least four years of work in the same areas.
  • Expertise in Integer or Mixed Integer Linear Programming, Constraint Programming, Convex Optimization, Multi-Objective Optimization, and established solvers such as Gurobi, Google OR-Tools, and CPLEX.
  • Significant experience implementing algorithms in C++ and using debuggers such as gdb to troubleshoot execution within a multi-threaded environment.

Responsibilities

  • Research, design, and implement state-of-the-art algorithms for optimal task allocation, scheduling, and temporal sequencing of heterogeneous teams of autonomous vehicles.
  • Improve existing C++-based mission planning software for use across disparate vehicle types and compute platforms.
  • Work with engineers, program managers, and product managers to define a technical roadmap for future autonomy solutions and SDK offerings.
  • Architect and write high-quality software for core systems, set software engineering standards, refine technical requirements, drive strategic technical improvements, and mentor other engineers.
  • Break down missions into assignable tasks based on agent capabilities, including navigating contested and denied environments and adapting to mission changes in real time.
  • Construct feasible and optimal action plans for distributed teams of autonomous vehicles while minimizing human operator workload.
  • Perform full software and hardware-in-the-loop simulation of complex multi-agent missions.

Desired Qualifications

  • Past publications on Optimization.

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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