Drimva

Shield AI

Autonomy Engineer- Behavior and Motion Planning (R6007)

San Diego, California · Full-time · Posted Oct 28, 2026

Experience
No general years requirement stated. Senior-level candidates: 5+ years of relevant professional experience with a master’s degree, or 4+ years with a PhD.
Education
Bachelor’s degree in computer science, engineering, applied mathematics, operations research, or a related field, or equivalent practical experience. For senior-level candidates: master’s degree in computer science, Robotics, or a related field, or PhD.

About the job

Develops and tests behavior and motion-planning algorithms and production software for autonomous systems operating in complex environments.

What you'll do

  • Research, design, and implement trajectory-planning and control algorithms for single- and multi-agent systems.
  • Build and test planning software, evaluating performance in simulation and, where applicable, on real hardware.
  • Collaborate on requirements, software architecture, integration, and delivery of autonomy capabilities.

What they ask for

  • Bachelor’s degree in a relevant field or equivalent practical experience.
  • Demonstrated experience building, testing, and debugging nontrivial C++ software in optimization, motion planning, robotics, autonomous systems, or a related algorithmic domain.
  • Experience with modern C++, concurrency debugging, Python, and software development on Linux.
  • Strong software engineering fundamentals, including algorithms, data structures, testing, debugging, version control, CI/CD, and maintainable design.

Nice to have

  • Experience with behavior or motion planning, multi-agent planning, trajectory optimization, or multi-objective optimization.
  • Experience with Gurobi, OR-Tools, CPLEX, VLMs/VLAs, or real-time, safety-critical autonomous systems.

Tools

C++, Python, Linux, Gurobi, OR-Tools, CPLEX, VLMs, VLAs

AI focus

May involve planning approaches incorporating vision-language models (VLMs), vision-language-action models (VLAs), or other learned components.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)