Robotics Engineer Intern

Location: Boulder, CO, United States Department: Ricoh Graphic Communication

Robotics Engineer Intern

Job Description

We are seeking a motivated and enthusiastic Robotics Engineer Intern to join our dynamic team at Ricoh USA for summer 2027. As a Robotics Engineer Intern, you will gain hands-on experience with advanced robotic systems, work directly with cutting-edge technologies, including simulation-driven robot training in NVIDIA Isaac Sim, and contribute to projects that push the boundaries of industrial automation.

Responsibilities

Assist in the design, development, and testing of robotic systems and components, with an emphasis on collaborative robot (cobot) platforms.

Contribute to the development of control architectures using ROS2, enabling higher-level autonomy and digital twin integration.

Develop and integrate sensor fusion techniques across multiple sensing modalities (e.g., cameras, depth sensors, LiDAR) for perception and safety.

Support algorithm development for computer vision, object detection, and pose estimation.

Assist in training, fine-tuning, and evaluating deep learning models for object detection and pose estimation using frameworks such as PyTorch, extending existing computer vision algorithm development work.

Collect and curate large-scale synthetic training data in NVIDIA Isaac Sim, leveraging domain randomization and automatic ground-truth labeling for bounding boxes, segmentation masks, depth, and object poses.

Support robot training in NVIDIA Isaac Sim / Isaac Lab, including reinforcement learning and imitation learning experiments for grasping, manipulation, and cobot motion tasks.

Contribute to sim-to-real transfer by validating simulation-trained perception models and policies on physical cobot hardware, and iterating on scene fidelity and randomization ranges to close the sim-to-real gap.

Contribute to system development on x86 platforms with NVIDIA GPU acceleration, while also evaluating embedded options (e.g., Jetson Orin) for potential cost, packaging, and performance benefits.

Support initiatives using NVIDIA Omniverse for visualization, simulation, and digital twin environments.

Support hardware and software integration across robotics, vision, production printers, and workflow systems to deliver cohesive automation solutions.

Document project progress and contribute to proof-of-concept demonstrations integrating robotics, vision, and simulation.

Qualifications

Enrolled in a Bachelor's or Master’s program in Robotics, Computer Engineering, Electrical Engineering, Computer Science, Mechanical Engineering, or related field.

Strong interest in robotics, automation, and applied AI.

Proficiency in Python and C/C++, with experience in robotics and vision libraries (e.g., ROS2, OpenCV, PCL).

Coursework, research, or project experience with deep learning for computer vision, including hands-on use of a framework such as PyTorch to train and evaluate models.

Understanding of sensors (cameras, LiDAR, depth) and hardware/software integration on robotic platforms.

Excellent problem-solving ability and attention to technical detail.

Ability to work independently and collaboratively across multidisciplinary teams.

Preferred Skills

Familiarity with collaborative robots (e.g., UR series) and robotic arm kinematics.

Experience with ROS2 middleware, simulation frameworks, and motion planning libraries.

Exposure to object detection and pose estimation methods for manipulation and localization tasks, including training or fine-tuning your own models rather than only running pretrained ones.

Hands-on experience with NVIDIA Isaac Sim or Isaac Lab, including synthetic data generation, domain randomization, or automatic ground-truth labeling.

Familiarity with reinforcement learning or imitation learning for manipulation and grasping, using toolkits such as Isaac Lab, Gymnasium, or Stable-Baselines3.

Awareness of sim-to-real transfer challenges and techniques for closing the gap between simulated and physical robot behavior.

Experience with GPU-accelerated computing on x86 and interest in exploring embedded platforms (e.g., Jetson) for optimized deployments.

Knowledge of computer graphics concepts and digital twin applications (e.g., NVIDIA Omniverse).

Research or project experience in embodied robotics and reinforcement learning.

Join us and be part of a passionate team advancing robotics automation, vision, simulation-based robot training, and digital twin technology for next-generation industrial solutions.

Ricoh is an EEO/Affirmative Action Employer -- Minorities/Women/Protected Veterans/Disabled.