AI/ML Engineer

Company Overview

Our client is a cutting-edge AI and robotics startup based in the UAE, specializing in autonomous systems for challenging heavy-duty environments. They design, develop, and implement intelligent autonomous technology end-to-end to assist enterprise customers with automation in complex and hazardous operational settings.

Role Summary

As an AI/ML Engineer, you will be responsible for developing the perception layer that allows autonomous vehicles to interpret their surroundings accurately under real-world conditions including dust, glare, heat, rugged terrain, and unmapped locations. This perception work is foundational for vehicle navigation, obstacle avoidance, and managing fleets. This is a hands-on position requiring high responsibility and early deployment of operational code on actual vehicles.

Key Responsibilities

• Create and implement a perception stack integrating camera, LiDAR, and radar sensor data.
• Develop algorithms for object detection, tracking, and segmentation robust to harsh outdoor and industrial environments.
• Build localization and mapping solutions capable of functioning effectively in GPS-denied or unmapped regions.
• Fuse multi-sensor data into a real-time, reliable environmental model for the planning system.
• Optimize machine learning models for edge hardware inference, adhering to strict latency and computational constraints.
• Design data processing pipelines for collection, annotation, validation, and continuous retraining based on fleet data.
• Provide perception insights to support mission planning and monitor fleet performance.
• Collaborate intensively with autonomy, controls, and hardware engineering teams to transition features from testing to production deployment.

Required Qualifications and Skills

• More than 3 years of experience developing perception systems deployed on real robots or vehicles, beyond curated datasets.
• Expertise in computer vision techniques including detection, tracking, and segmentation from live sensor input.
• Proven hands-on experience with SLAM, point cloud processing, and multi-sensor calibration.
• Experience working with sensor fusion methodologies, such as Kalman filtering, factor graphs, or learned fusion.
• Proficiency in Python and C++ programming languages.
• Experience deploying AI models to edge or embedded GPU platforms.
• Familiarity with ROS/ROS 2 frameworks and conducting field tests.
• Strong sense of ownership and responsibility.

Desirable Skills

• Knowledge of model compression and optimization techniques like quantization, pruning, and TensorRT.
• Experience with fleet data management infrastructure and MLOps practices for continuous model enhancement.
• Familiarity with simulation tools for perception algorithm testing.

Why Join

• Work on technology deployed in real vehicles operating on genuine missions.
• Opportunity to take early ownership in a rapidly expanding startup.