Senior Robotics Software Engineer, Motion Planning

General Motors United State
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AI Summary

Join the AI Research team in the Autonomous Robotics Center (ARC) to develop motion planning and collision avoidance capabilities for manufacturing manipulation systems. As a Senior Robotics Software Engineer, you will own planning scene and collision-checking integration, develop motion planning pipelines, and define collision avoidance strategies. This role requires 5+ years of experience in motion planning and collision avoidance systems for robotic manipulators.

Key Highlights
Motion planning and collision avoidance for manufacturing manipulation systems
Planning scene and collision-checking integration
Motion planning pipeline development
Key Responsibilities
Own planning scene and collision-checking integration for robotic manipulation workcells
Develop and tune motion planning pipelines to improve success rate, cycle time, and recovery robustness
Define collision avoidance strategies and performance guardrails
Technical Skills Required
C++ Python ROS 2 MoveIt2 OMPL-based sampling planners Trajectory optimization approaches
Benefits & Perks
Relocation package provided
Full-time employment
Benefits overview
Nice to Have
Production experience with ROS 2 and MoveIt2
Experience working in dynamic environments and integrating safety considerations

Job Description


Job Description

We are seeking a Senior Robotics Software Engineer, Motion Planning to join the AI Research team in the Autonomous Robotics Center (ARC). In this role, you will own the motion planning and collision avoidance capabilities for manufacturing manipulation systems—from planning scene representation and collision checking to planner configuration, runtime performance, and safe recovery behaviors.

ARC’s AI Research team is building end-to-end robot policies that enable dexterous manipulation in real-world manufacturing environments. We advance embodied AI by integrating multimodal perception, robot learning architectures, and physical robotic systems to solve manipulation, autonomy, and simulation challenges at industrial scale.

Work Arrangement

  • Onsite, full-time (Warren, MI)
  • Occasional travel to manufacturing plants or pilot cells as needed


What You’ll Do

  • Own planning scene and collision-checking integration for robotic manipulation workcells, including robust world modeling updates and constraint handling.
  • Develop and tune motion planning pipelines (e.g., OMPL-based sampling planners and/or trajectory optimization approaches) to improve success rate, cycle time, and recovery robustness.
  • Define collision avoidance strategies and performance guardrails, including discretization tolerances, validation thresholds, safety buffers, and regression criteria.
  • Integrate trajectory generation with low-level controllers and execution systems, ensuring correct interfaces for joint trajectories, gripper actions, and execution monitoring.
  • Build reliable recovery behaviors for plan or execution failures, including re-planning strategies, safe retreat logic, and consistent fault reporting for downstream analysis.
  • Partner closely with AI/ML and validation teams to define upstream and downstream interface contracts and translate field failures into continuous planning improvements.


Required Qualifications

  • B.S. or M.S. in Robotics, Computer Engineering, Computer Science, or a related field.
  • 5+ years of experience developing motion planning and collision avoidance systems for robotic manipulators, with deployment exposure in real-world workcells.
  • Strong programming experience in C++ and/or Python with solid software engineering practices in multi-module robotics systems.
  • Hands-on experience with planning frameworks and collision-checking concepts (e.g., MoveIt planning scene, collision world, planner interfaces).
  • Experience integrating planning systems with controllers and execution layers, including trajectory execution, controller configuration, and runtime monitoring.
  • Strong hardware debugging skills including logging, root cause analysis, and systematic performance tuning.


Preferred Qualifications

  • Production experience with ROS 2 and MoveIt2, including planning scene updates and controller integration.
  • Experience working in dynamic environments (moving obstacles, human-aware constraints) and integrating safety considerations.
  • Familiarity with industrial robotics integration patterns, including PLC interfaces, safety-rated stops, and cell interlocks.
  • Experience developing integration or system tests for multi-node robotics systems.


This role is categorized as onsite. This means the selected candidate is expected to report to a specific location on a full-time basis. This job may be eligible for relocation benefits.

About GM

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Why Join Us

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Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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