General Motors is seeking highly motivated interns to join their Robotics Software team, focusing on the development of autonomous robotic systems. The intern will engage in hands-on experimentation, algorithm development, and integration of multi-modal sensor data to enhance AI-driven robotic solutions.
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
Skills
- 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
- 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
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
Company Overview
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