Robotics Software Development Intern

Build and deploy real-world robotics perception pipelines at Robolabs AI. You'll work hands-on with state-of-the-art computer vision models and ROS2 on physical hardware — bridging the gap between research prototypes and production-ready systems.

What You'll Do

●Develop and integrate computer vision pipelines using models like YOLO, SAM, and DETR for real-time robotic perception
●Write and maintain ROS2 nodes in Python and C++ for sensor processing, object detection, and navigation
●Work directly with hardware — cameras, LiDARs, robotic arms, and mobile platforms — in our Gurgaon lab
●Profile, optimize, and deploy vision models on edge devices for real-time inference
●Collaborate with the engineering team to test, debug, and iterate on robotic systems end to end
●Document experiments, results, and technical decisions clearly

What We're Looking For

●Pursuing or recently completed a degree in Robotics, Computer Science, Electrical Engineering, or a related field
●Hands-on experience with computer vision frameworks — YOLO, SAM, DETR, or similar transformer/CNN-based models
●Proficiency in Python and working knowledge of C++ for robotics applications
●Familiarity with ROS2 (nodes, topics, services, launch files, TF2)
●Comfortable working at the hardware-software interface — not afraid of cables, sensors, or debugging on a physical robot
●Strong fundamentals in linear algebra, probability, and 3D geometry
●Self-driven and comfortable in a fast-paced, early-stage environment

Nice to Have

●Real-world project experience — personal, academic, or competition-based — involving robotic systems or CV pipelines
●Published research papers or conference contributions in computer vision, robotics, or related areas
●Experience with simulation tools (Gazebo, Isaac Sim, MuJoCo) for sim-to-real transfer
●Familiarity with model optimization techniques — TensorRT, ONNX, quantization
●Contributions to open-source robotics or computer vision projects
●Experience with depth estimation, SLAM, or 3D point cloud processing

How to Apply

Send your resume and a short note about why this role excites you to [email protected] with the subject line "Application: Robotics Software Development Intern". Include links to your GitHub, published papers, or any project demos that showcase your work.

What You'll Do

●Develop and integrate computer vision pipelines using models like YOLO, SAM, and DETR for real-time robotic perception

●Write and maintain ROS2 nodes in Python and C++ for sensor processing, object detection, and navigation

●Work directly with hardware — cameras, LiDARs, robotic arms, and mobile platforms — in our Gurgaon lab

●Profile, optimize, and deploy vision models on edge devices for real-time inference

●Collaborate with the engineering team to test, debug, and iterate on robotic systems end to end

●Document experiments, results, and technical decisions clearly

What We're Looking For

●Pursuing or recently completed a degree in Robotics, Computer Science, Electrical Engineering, or a related field

●Hands-on experience with computer vision frameworks — YOLO, SAM, DETR, or similar transformer/CNN-based models

●Proficiency in Python and working knowledge of C++ for robotics applications

●Familiarity with ROS2 (nodes, topics, services, launch files, TF2)

●Comfortable working at the hardware-software interface — not afraid of cables, sensors, or debugging on a physical robot

●Strong fundamentals in linear algebra, probability, and 3D geometry

●Self-driven and comfortable in a fast-paced, early-stage environment

Nice to Have

●Real-world project experience — personal, academic, or competition-based — involving robotic systems or CV pipelines

●Published research papers or conference contributions in computer vision, robotics, or related areas

●Experience with simulation tools (Gazebo, Isaac Sim, MuJoCo) for sim-to-real transfer

●Familiarity with model optimization techniques — TensorRT, ONNX, quantization

●Contributions to open-source robotics or computer vision projects

●Experience with depth estimation, SLAM, or 3D point cloud processing