Senior Perception Engineer

Micropolis Holding

Dubai

On-site

AED 300,000 - 500,000

Full time

5 hours ago
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Job summary

Micropolis Holding seeks a Senior Perception Engineer to train and optimize deep learning models for autonomous platforms across urban, closed community, and off-road environments. You will process LiDAR, camera, and radar data, building 3D object detection, segmentation, and tracking.

You’ll deploy at scale using PyTorch and modern ML tools, validating with real-world tests on self-driving vehicles. The role emphasizes collaboration, hands-on development, and rapid learning in a cutting-edge

Qualifications

  • 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.

Responsibilities

  • Train and optimize deep 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 key perception tasks, including 3D object detection, 3D semantic segmentation, multi-object tracking, parking slot detection, and cost map.
  • Work with large-scale datasets and state-of-the-art machine learning models using in-house compute infrastructure.
  • Validate, benchmark, and iterate on perception algorithms through real-world testing on self-driving vehicle platforms.

Skills

Python
PyTorch
LiDAR data processing
Computer vision
Transformer architectures
C++14/17

Education

Bachelor’s or Master’s degree in CS/Robotics/Mechatronics

Tools

TensorRT
ONNX
LibTorch

Job description

We are looking for a Senior Perception Engineer to train and optimize the deep learning models that let our autonomous platforms see — across urban, closed community, and off-road environments. We are looking for a Senior Perception Engineer to train and optimize the deep learning models that let our autonomous platforms see — across urban, closed community, and off-road environments.

Role Responsibilities
  • Train and optimize deep 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 key perception tasks, including 3D object detection, 3D semantic segmentation, multi-object tracking, parking slot detection, and cost map.
  • Work with large-scale datasets and state-of-the-art machine learning models using in-house compute infrastructure.
  • Validate, benchmark, and iterate on perception algorithms through real-world testing on self-driving vehicle platforms.
Required Qualifications
  • 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.
Preferred Qualifications
  • 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 TensorRT, ONNX, or LibTorch.
  • Proven experience building and maintaining scalable ML systems using collaborative practices such as MLOps, data/version management, and CI/CD pipelines.
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