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Job Description & How to Apply Below
Location: Dubai, United Arab Emirates (Micropolis Robotics)
Role ResponsibilitiesIn this role, you will:
- Train and optimizedeep learning models that process multi-modal sensor data, including LiDAR point clouds, multi-view camera images, and radar signals.
- Work on multiple autonomous driving stacks including
urban
,
closed community
, and
off-road environments. - Develop and improve keyperceptiontasks, including3D object detection,3D semantic segmentation,Multi-objecttracking,Parking slot detection, andCost map
- Work with large-scale datasets and state-of-the-art machine learning models using in-house compute infrastructure.
- Validate, benchmark, and iterate on perceptionalgorithms through real-world testing on self-driving vehicle platforms.
- Minimum 3+ years of experience in Perception systems.
- Bachelor’s or Master’s degree in Computer Science, Robotics, Mechatronics, or related field.
- Hands-on experience with deep learning applied to at least one sensing modality (camera, LiDAR, or radar).
- Familiarity with modern deep learning architectures, preferably including transformer-based models (e.g., Vision Transformers - ViT).
- Strong practical experience with PyTorch.
- Proficient programming skills in Python.
- Strong teamwork and communication skills, with a proactive and learning-oriented mindset.
- Strong programming skills in modern C++ 14/17.
- Experience working on autonomous driving or robotics perception systems.
- Experience with optimized model deployment frameworks such as Tensor
RT, ONNX, or Lib Torch. - Proven experience building and maintaining scalable ML systems using collaborative practices such as MLOps, data/version management, and CI/CD pipelines.
Position Requirements
10+ Years
work experience
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