Your Mission
You will support the team in:
- Developing and testing algorithms for object detection, segmentation, and classification.
- Supporting multi-object tracking, free-space detection, obstacle detection, and environment understanding tasks.
- Assisting in sensor fusion workflows using data from LiDAR, Radar, Camera, USS, IMU, or GNSS.
- Supporting localization, SLAM, HD mapping, occupancy grids, semantic maps, and motion prediction tasks.
- Helping build navigation support algorithms for autonomous and robotic systems.
- Preparing and analyzing datasets for perception, mapping, localization, and simulation workflows.
- Supporting automated data labeling, analytics pipelines, replay tools, and synthetic data pipelines.
- Creating and validating simulation scenarios using CARLA, robotics simulators, or custom environments.
- Supporting closed-loop testing and virtual validation for autonomy stacks.
- Developing and integrating software modules using ROS / ROS2.
- Interfacing with sensors, robotic controllers, edge computers, embedded systems, and software platforms under the guidance of senior engineers.
- Documenting experiments, test results, algorithm performance, and technical findings.
Who You Are
You should have:
- B.Sc., or be in the final year of completing a degree, in Robotics, Computer Engineering, Electrical Engineering, Artificial Intelligence, Mathematics, Computer Science, Mechatronics, or a related technical field.
- Strong academic foundation in algorithms, mathematics, robotics, AI, or autonomous systems.
- Good understanding of linear algebra, probability, optimization, and computer vision fundamentals.
- Good coding skills in Python and/or C++.
- Basic knowledge of ROS / ROS2.
- Familiarity with simulation tools such as CARLA or other robotics simulation platforms is a plus.
- Interest in robotics, autonomous driving, drones, warehouse robotics, mapping, SLAM, sensor fusion, AI, or deep learning.
Qualifications & Mindset
You should be:
- A fresh graduate or final-year student eligible for a structured internship.
- Curious about how perception, localization, mapping, and navigation algorithms work in real-world systems.
- Comfortable learning new tools, reading technical documentation, and applying research concepts.
- Able to work across simulation, testing, data preparation, and software integration tasks.
- Strong in problem-solving, debugging, and analytical thinking.
- Detail-oriented when evaluating performance, accuracy, and real-world constraints.
- Able to collaborate with software, embedded, robotics, and product teams.
- Self-driven, eager to learn, and able to take ownership of assigned tasks.
Nice to have
- Previous academic, graduation, or personal projects in robotics, autonomous systems, computer vision, SLAM, or sensor fusion.
- Experience with ROS / ROS2 projects.
- Experience with CARLA, Gazebo, Isaac Sim, or similar simulation tools.
- Experience with Python libraries for AI, computer vision, or data analysis.
- Familiarity with AI / deep learning models for perception, tracking, or prediction.
- Basic understanding of edge computing or embedded systems.
- Familiarity with data pipelines, annotation workflows, or automated data labeling.
- Exposure to real-time perception, navigation pipelines, or multi-sensor calibration.
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