Senior Robotics Software Engineer – AI-Enabled Manipulation & Industrial Automation

General Motors•Mountain View, CA

2d•$153,200 - $234,100•Onsite

About The Position

The Senior Robotics Software Engineer designs, develops, integrates, validates, and deploys AI-enabled robotic applications for industrial and factory automation. The role spans robotic manipulation, perception, motion planning, computer vision, simulation, controls, and AI, including vision-language-action (VLA) models and learned manipulation policies. The engineer develops end-to-end, closed-loop systems combining classical robotics and modern AI for perception-guided manipulation, multimodal task understanding, sensor-driven feedback, and autonomous execution. The position focuses on turning advanced prototypes into robust, scalable, production-relevant systems, with technical ownership from early prototyping and simulation through hardware integration, validation, and deployment. The role is categorized as onsite and is based in Mountain View, California. The selected candidate is expected to report to a specific location five days per week on a full-time basis.

Requirements

Master’s degree in Computer Science, Robotics, Mechanical, Electrical, or Computer Engineering, Artificial Intelligence, Machine Learning, or a related technical field.
At least 2 years of experience developing robotic software or applications involving manipulation, perception, motion planning, simulation, industrial automation, or related systems.
Strong Python, C++, and ROS 2 development skills, with experience building modular robotics software.
Familiarity with AI/ML workflows for robotic perception, learned manipulation, multimodal robotics, and autonomous systems.
Strong understanding of robotic manipulation, perception, motion planning, controls, coordinate frames and transformations, simulation, and automation software.
Experience with inverse kinematics, trajectory generation and execution, collision checking, robot state representation, gripper control, and integration of manipulators, sensors, and other automation hardware.
Experience developing or integrating perception systems for detection, segmentation, pose estimation, RGB-D, point clouds, or grasp generation, and integrating AI/perception models into real-time or near-real-time applications.
Experience debugging complex robotic systems across software, simulation, AI, networking, and physical hardware interfaces.
Strong analytical, troubleshooting, communication, and technical documentation skills, with the ability to independently manage complex assignments and collaborate across disciplines.

Nice To Haves

At least 5 years of experience in robotics software, industrial robotics, AI-enabled robotics, manipulation, or automation systems.
Experience with FANUC, Universal Robots, collaborative or industrial manipulators, grippers, wrist-mounted cameras, depth sensors, industrial automation, material handling, robotic pick-and-place, machine tending, factory simulation, virtual commissioning, or plant-floor robotic applications.
Experience with MoveIt/MoveIt Task Constructor, Lula, RMPflow, OMPL, NVIDIA Isaac Sim/Isaac Lab, Omniverse Replicator, or similar frameworks.
Experience with VLA models, multimodal robotics, imitation learning, learned manipulation policies, synthetic data, domain randomization, automated annotation, simulation-to-real transfer, or simulated-environment training.
Experience with 3D perception, including RGB-D, point clouds, 6D pose estimation, registration, and geometric computer vision.
Experience deploying AI models with PyTorch, TensorRT, ONNX Runtime, or comparable GPU-accelerated inference frameworks.
Experience optimizing control-loop timing, perception and inference latency, trajectory execution, and end-to-end task cycle time.
Experience taking robotic systems from research or prototype environments through integration, validation, and deployment in production or manufacturing settings.

Responsibilities

Design and deploy robotic applications for industrial automation, including pick-and-place, material handling, part transfer, machine tending, inspection support, and vision-guided manipulation.
Build collision-aware, dynamically feasible manipulation pipelines integrating object detection and pose estimation, grasp generation, inverse kinematics, motion and trajectory planning, collision avoidance, reliable execution, and gripper control.
Develop computer-vision and AI perception systems for detection, semantic and instance segmentation, 6D pose estimation, RGB-D and point-cloud processing, scene understanding, and grasp-point generation.
Integrate AI/ML models into real-time or near-real-time robotic workflows to improve perception, generalization, manipulation, task-level decision-making, and runtime reliability.
Develop closed-loop robotic systems that use sensor feedback to monitor task execution, detect failures, update robot actions, and improve runtime reliability.
Develop and evaluate VLA models and learned policies for multimodal task understanding, natural-language instruction following, action generation, imitation learning, and autonomous manipulation.
Use NVIDIA Isaac Sim, Isaac Lab, Omniverse, Replicator, and related tools to build digital environments, generate synthetic data, validate behavior, and develop simulation-to-real workflows.
Own robotic software architecture across perception, planning, control, simulation, AI inference, data flow, system interfaces, hardware integration, and deployment; develop modular, maintainable software.
Integrate and calibrate manipulators, grippers, RGB/RGB-D and depth cameras, force/torque sensors, and other automation hardware, including camera intrinsics/extrinsics, hand-eye calibration, and robot-to-cell registration.
Implement force and compliant control, such as impedance, admittance, and guarded moves, for contact-rich tasks including insertion and assembly.
Build data-collection workflows for learned policies, including teleoperation, demonstration capture, dataset curation, and experiment tracking.
Debug and validate systems across software, AI models, perception, simulation, motion planning, controls, networking, and hardware; define measures such as task success, perception accuracy, cycle time, trajectory quality, repeatability, and reliability.
Collaborate with robotics, perception, ML, controls, manufacturing, and plant-facing teams to troubleshoot issues, document solutions, and transition prototypes through hardware integration, validation, and deployment.
Provide technical ownership of robotic applications from early prototyping and simulation through hardware integration, validation, and deployment.
Optionally integrate robotic cells with industrial systems and safety infrastructure, including PLCs, safety I/O, and robot safety configurations in accordance with ISO 10218 and ISO/TS 15066.

Benefits

Medical insurance
Dental insurance
Vision insurance
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts
Incentive pay program with payouts based on company performance, job level, and individual performance