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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer focused on Navigation - **Company:** Agility Logistics Corp. - **Location:** Pittsburgh, PA, United States - **Experience:** Expert - **Salary:** $155,000.0 - $241,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Software Debugging, Kinematics, Motion Planning, Routing, Regression Testing, Spatial Data Infrastructures, Reinforcement Learning, Multithreading, Multi-Agent Systems, C++14, Lidar - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/31dea310-f9ed-44b3-b610-4453b356e715 ## About the Role * 5+ years of professional experience in robotics, specifically developing and deploying real-time navigation and motion planning systems for autonomous mobile platforms (humanoids, quadrupeds, autonomous vehicles). * Expertise in 3D/volumetric map representations (e.g., octomaps, voxel grids) for local path planning and collision avoidance. * Deep technical understanding of locomotion-specific path and motion planning algorithms, including sampling-based planners (RRT/PRM), optimization-based methods (MPC/LQR), and hybrid A*. * Expert proficiency in modern C++ (C++17/20), with a proven track record of writing high-performance, multithreaded code for robotics applications. * Experience with common robotics frameworks (e.g., ROS/ROS2, DDS) and hands-on experience with modern optimization libraries relevant to motion planning (e.g., Ceres, IPOPT, OSQP). * Proven ability to systematically test and debug systems on physical robots, and integrate perceived environment data (LiDAR, camera, depth sensing) into the planner., * Experience training and deploying Reinforcement Learning (RL) agents for complex locomotion behaviors. * Hands-on experience implementing Model Predictive Control (MPC) or similar optimization-based control techniques for dynamic robot locomotion. * Familiarity with perception pipelines and the integration of perceived environment data into the planning stack. * Experience with GPU-accelerated spatial data structures (e.g., NVBlox, specialized CUDA implementations) for high-throughput, low-latency map updates and querying. * Strong foundational knowledge of robot kinematics, dynamics, controls, and state estimation (e.g., EKF, particle filters). * Experience with multi-robot coordination/route planning and abiding by boundary constraints in a workcell map. * Experience with multi-robot mapping and localization, including map persistence and sharing capabilities. * Publications in top-tier robotics conferences (ICRA, RSS, IROS, CoRL). This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future. ## Description Join the Autonomy team as a Senior Software Engineer focused on Navigation. You will be a core contributor, driving the design and deployment of real-time motion planning and navigation systems that empower our humanoid robots to operate robustly and autonomously in complex logistics and manufacturing environments. This is a high-impact role essential to scaling our commercial deployments, improving the efficiency of autonomous loco-manipulation behaviors, and achieving software readiness for the next generation robot platforms. About The Work * Design, implement, and deploy 3D motion planning algorithms for locomotion, with an emphasis on whole-body collision-aware motion execution in real-time. * Own the core components of our navigation stack, specifically the local planning maps, terrain models, and grid map representations used for path and motion planning with collision avoidance. * Advance our locomotion capabilities by developing and maintaining a 3D footstep path planner aiming to significantly reduce navigation cycle times. * Define and implement the necessary navigation features and route planning algorithms to enable coordinated movement and resource sharing within multi-agent robot fleets. * Drive the maturity of our release processes by designing, implementing, and maintaining robust regression testing pipelines for motion planning and navigation modules. * Collaborate with the AI and Controls teams to integrate locomotion behaviors with RL policies and support whole-body control. * Integrate and debug planning algorithms on real-world hardware, owning the transition from simulation environments (e.g., Gazebo, MuJoCo, Isaac Sim) to physical robots. ## Related Videos - [How to develop an autonomous car end-to-end: Robotic Drive and the mobility revolution](https://www.wearedevelopers.com/videos/22-how-to-develop-an-autonomous-car-end-to-end-robotic-drive-and-the-mobility-revolution) - [Robots are coming into the wild! 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