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Engineer - Perception (Deep Learning) (m/f/d)
Permanent
Abu Dhabi, United Arab Emirates
23.06.2026
Role Overview Seeking a Perception Engineer to develop and enhance a perception stack using both classical computer vision techniques and modern deep learning approaches. The role focuses on end-to-end learning systems while maintaining strong grounding in traditional methods. The work supports real-time, deployable perception systems for autonomous navigation across diverse environments and robotic platforms.
Key Responsibilities
Design and implement robust, real-time perception modules for both structured (on-road) and unstructured (off-road) environments using learning-based and geometric methods.
Develop clean, modular, and efficient code in C++ and Python, following ROS1/ROS2 and industry best practices.
Conduct extensive field testing and iterative system tuning to ensure performance and reliability under real-world conditions.
Work closely with adjacent system components such as localization, planning, and control to enable seamless integration.
Participate in code reviews and maintain clear, detailed technical documentation.
Integrate HD map data (e.g., Lanelet2 and semantic layers) into perception pipelines to support object-level reasoning, localization, and terrain adaptation.
Minimum Qualifications and Skills
Bachelor’s or Master’s degree in Robotics, Computer Vision, or a related field.
4+ years of experience in real-time perception or computer vision systems.
Proficiency with libraries and tools such as OpenCV, PCL, Open3D, PyTorch, and TensorRT.
Strong understanding of deep learning architectures (e.g., CNNs, transformers) and their application in perception tasks.
Familiarity with modern perception approaches such as LSS, BEVFormer, BEVFusion, and ability to assess trade-offs between accuracy, latency, and deployability.
Strong programming skills in Python and C++, with experience in ROS1 or ROS2 systems.
Experience with modern development workflows and tools such as Git, Docker, and CI/CD systems.
Preferred Qualifications and Skills
Experience combining traditional perception techniques with deep learning-based methods.
Familiarity with experiment management and MLOps tools such as Hydra, Weights & Biases, AWS SageMaker, or GCP.
Knowledge of HD map frameworks such as Lanelet2 or similar systems.
Experience working with ARM64-based edge devices, including NVIDIA Jetson platforms.
Additional Skills
Strong communication skills with the ability to explain complex technical concepts clearly.
Ability to work independently in fast-paced environments.
Comfortable balancing experimental prototyping with debugging real-world system challenges
Engineer - Perception (Deep Learning) in Abu Dhabi, United Arab Emirates
