2026 Summer Intern – Software Engineer, Autonomous Robot (Masters Degree)

Summary: General Motors is seeking highly motivated interns to research, explore, and evaluate cutting-edge AI-driven approaches for robot localization, perception, and motion planning. The role involves hands-on experimentation, algorithm development, and integration of multi-modal sensor data to advance autonomous robotic systems. Responsibilities: - Evaluate and test LiDAR-based localization repositories - Investigate Gaussian splatting localization pipelines and assess feasibility for embedded platforms - Explore machine-learning techniques for feature point correspondence between image frames - Implement and benchmark place recognition algorithms using computer vision - Integrate dynamic object handling into localization workflows - Develop multi-agent map-building and construction processes (offboard) - Design sensor fusion strategies for heterogeneous modalities (e.g., 3D LiDAR, 2D LiDAR, monocular camera, IMU, wheel odometer) - Apply post-processing optimization algorithms (e.g., factor graph and pose graph) - Create, curate, and manage datasets for training AI models - Ensure data quality and diversity for robust algorithm development - Upgrade the existing simulation environment to support generation of realistic 3D LiDAR data and photorealistic image rendering for advanced perception testing - Design and implement adversarial scenarios to identify potential safety vulnerabilities and enhance overall system robustness - Develop perception solutions leveraging joint representation of Bird’s Eye View (BEV) and DETR-based object detection using multi-modality inputs - Enhance robustness in perception pipelines for dynamic environments - Research and implement denoising diffusion-based motion planning algorithms - Reinforcement learning in simulation engine to improve path generation policy - Evaluate performance and scalability of AI-driven planning approaches in real-world scenarios - Design and implement high-precision localization methods using camera, LiDAR, wheel encoder and inertial sensors - Develop scalable and real-time localization module optimized for autonomous robotic systems - Create engineering specifications and test procedures to ensure system compliance - Evaluate and benchmark the performance of systems - Review the state-of-the-art in camera- and LiDAR-based algorithms - Troubleshoot using strong knowledge of probabilistic estimation, sensor fusion, and real-time system implementation - Adjust and fine-tune system parameters to improve accuracy and robustness Required Qualifications: - Currently enrolled in a Masters Degree and completed at least 1 year of Masters in Robotics, Computer Science, Electrical/Mechanical Engineering, or related technical fields - Proficiency in C++ or Python - Adhere to continuous development and deployment practices in robotic software development - Expertise in one or more of the technical areas: Camera- and LiDAR-based localization algorithms, statistical estimation theory, and practices such as pose graph and factor graph optimization and implementation - Understanding state-of-the-art solutions in place recognition for addressing loop-closure detection issues - Perception, e.g., feature embedding, object detection, bird's eye view (BEV) semantic representation - Motion path planning algorithms, e.g., Nav2 - Simulation engines: e.g., IsaacSim, IsaacLab, and etc - Dataset curation and annotation tools - Experience optimizing algorithm/software to balance performance within resource constraints - Familiarity with ROS2 or other robotics middleware Preferred Qualifications: - Machine learning knowledge and practice experience - Proficiency with deep learning frameworks and toolchains like PyTorch and TensorFlow - Familiarity with repositories like DETR, BEVformer, BEVfusion, SAMv2, Ceres Library/GTSAM, ORB-SLAM, VINS-Mono, and etc - Experience working with cloud-based data collection and data pipeline systems - AV/ADAS integration or industrial automation experience is a bonus - Graduating between December 2026 and June 2027 Required Skills: C++, Python, Camera-based localization, LiDAR-based localization Important Skills: Machine learning, Deep learning frameworks, ROS2, Motion planning algorithms, Simulation engines Nice-to-Have Skills: Data engineering, Dataset curation, Soft skills Internship Start Date: Start in 2026 Summer Benefits: Paid US GM Holidays, GM Family First Vehicle Discount Program, Result-based potential for growth within GM, Intern events to network with company leaders and peers