R&D Robotics & Artificial Intelligence Intern

About the Role

We are looking for two highly motivated and hands-on Robotics & AI Interns to join our research and development team. In this role, you will work at the cutting edge of physical AI, developing advanced software pipelines that enable intelligent systems to perceive their environments with high fidelity and execute complex, autonomous tasks.

This internship is designed for individuals who want to bridge the gap between state-of-the-art computer vision algorithms, modern deep learning architectures, and physical (or simulated) robotic platforms.

Core Responsibilities

You will collaborate with our engineering team to develop, test, and deploy software across our perception and autonomy stacks:

• Advanced Perception & Spatial Computing: Design and implement robust algorithms for environment reconstruction, scene understanding, and sensor processing. You will manipulate real-time data from depth sensors (RGB-D, LiDAR) to create spatial awareness for our platforms.
• Embodied AI & Intelligent Control: Develop, train, and deploy advanced learning-based policies for robotic systems. You will focus on multi-modal intelligence, enabling agents to translate complex sensory inputs into precise autonomous actions.
• Simulation & Physical Deployment: Build, configure, and utilize simulation environments (e.g., Isaac Sim, MuJoCo, PyBullet) to train and validate perception and control pipelines before deploying code onto hardware.
• Systems Integration: Benchmark, optimize, and integrate deep learning models with classic robotics frameworks to ensure real-time, low-latency performance.

Technical Requirements

• Education: Pursuing a BS, MS, or PhD in Robotics, Computer Science, Computer Engineering, or a related technical field.
• Computer Vision & 3D Processing: Strong hands-on experience with OpenCV for image processing and PCL (Point Cloud Library) or Open3D for point cloud filtering, segmentation, and registration. Solid grasp of 3D geometry and coordinate transformations.
• Deep Learning & AI: Deep understanding of Neural Networks, with specific technical expertise in Transformer architectures, multi-modal models (Vision-Language), and attention mechanisms.
• Software Engineering: High proficiency in Python and/or C++, with strong clean-coding practices, Git version control, and comfort working within Linux/Ubuntu environments.
• Robotics Frameworks: Experience or familiarity with ROS/ROS2, imitation learning, behavioral cloning, or reinforcement learning applied to autonomous systems.

Nice-to-Haves

• Experience working directly with physical robotic hardware or deployment pipelines.
• Experience with generative AI, diffusion models, or open-source foundation models.
• Active contributions to open-source robotics, computer vision, or AI projects on GitHub.