Perception & Autonomy Engineer for Edge Robotics

Tanqeeb; Dubai; On-site; AED 250,000 - 450,000; Full time

Job summary

Tanqeeb in Dubai seeks an AI/ML Engineer to own the perception stack for autonomous vehicles. You will fuse camera, LiDAR and radar data to create a reliable environment model used by planning and navigation systems.

You will work with Python and C++, deploy models to edge hardware, and collaborate with autonomy, controls and hardware teams to move features from test tracks to real missions.

Qualifications

• 3+ years building perception systems on real robots or vehicles
• Strong CV skills: detection, tracking, segmentation on live sensors
• Hands-on SLAM, point cloud processing and multi-sensor calibration
• Experience with sensor fusion (Kalman filtering, factor graphs or learned fusion)
• Strong Python and C++
• Experience deploying models to edge or embedded GPU hardware
• Comfort with ROS/ROS 2 and field testing
• Ownership mindset

Responsibilities

• Design, build and deploy the perception stack across camera, LiDAR and radar inputs
• Develop object detection, tracking and segmentation that holds up in harsh outdoor and industrial settings
• Build localisation and mapping capability, including operation in GPS-denied and unmapped areas
• Fuse multi-sensor data into a unified, real-time environmental model the planning stack can trust
• Optimise models for on-vehicle inference on edge hardware within strict latency and compute budgets
• Build data pipelines for collection, labelling, validation and retraining from fleet data
• Feed perception insights into fleet-level analytics for mission planning and performance monitoring
• Work closely with autonomy, controls and hardware engineers to take features from test track to deployment

Skills

Perception systems

Python

C++

Computer vision

Sensor fusion

ROS/ROS 2

Ownership mindset

Tools

ROS/ROS 2

Kalman filtering

Point cloud processing

Job description

Tanqeeb in Dubai seeks an AI/ML Engineer to own the perception stack for autonomous vehicles. You will fuse camera, LiDAR and radar data to create a reliable environment model used by planning and navigation systems.

You will work with Python and C++, deploy models to edge hardware, and collaborate with autonomy, controls and hardware teams to move features from test tracks to real missions.