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ForterraForterraClarksburg, MD

Path Planning Engineer

Develops real-time path and motion planning algorithms in C++ for autonomous vehicles, integrates with on-vehicle systems like perception and controls, and validates through simulation, HIL, and field testing. Requires strong C++ skills, robotics background, and hands-on deployment experience.

150k – 180k/yr
On-siteEmbedded Engineering

About the role

What you'll do

  • Develop real-time (deterministic, randomized, and optimization-based) path and motion planning algorithms for various vehicle types (Ackermann, skid-steered, wheeled, tracked) using C++ in a Linux environment
  • Integrate planning algorithms with on-vehicle systems, including perception, localization, controls, and platform interfaces
  • Deploy, test, and debug autonomy software directly on vehicles, addressing real-time constraints, system latency, and hardware limitations
  • Design and implement messaging for synchronization, logging and debugging across distributed systems
  • Own end-to-end validation: simulation → HIL → on-vehicle testing, ensuring consistency and performance across environments
  • Diagnose and resolve issues observed in field testing, including edge cases arising from sensing, actuation, and environment variability
  • Work closely with cross-functional teams (Perception, Controls, Platform, Systems Engineering) to ensure robust and reliable vehicle behavior
  • Travel up to 20% to support on-site vehicle integration and testing

Qualifications

  • BS, MS, or PhD in Robotics, Applied Mathematics, Mechanical Engineering, Computer Science, or related field
  • Strong background in path planning, motion planning, or related autonomy domains
  • Strong programming skills in C++
  • Solid software engineering fundamentals: system design, unit/integration testing, debugging
  • Experience deploying or integrating software on physical robotic or automotive platforms
  • Ability to deliver production-quality software in a continuously integrated environment
  • Demonstrates clean, maintainable code and documentation practices
  • Strong problem-solving skills with a proactive, hands-on approach

Preferred Qualifications

  • Prior experience with unmanned ground vehicles operating in outdoor environments
  • Experience with on-vehicle debugging, telemetry analysis, and real-time system profiling
  • Familiarity with robotics middleware (e.g., ROS/ROS2 or similar frameworks)
  • Experience working across perception–planning–controls interfaces
  • Expertise with GPU or ML toolkits such as CUDA, PyTorch, TensorFlow, and/or TensorRT

Compensation

US Salary Range: $150,000—$180,000 Equity included. Competitive benefits: premium healthcare (80% covered), life/disability insurance, PTO (20 days), parental leave (7 weeks), tuition reimbursement ($9k), 401(k) with 4% match.

Skills

C++LinuxROSros2CUDAPyTorchTensorFlowTensorRTpath planningmotion planning

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