Edge AI & Robotics Systems Lead

Careernet; Ajman; On-site; AED 367,000 - 661,000; Full time

Job summary

Careernet in Ajman, UAE, is seeking an AI Lead Engineer to architect and lead the intelligent software layer for an AI and robotics system. You will drive integration of AI models with perception, decision-making, and robotic execution in edge/on-premise environments.

The role requires hands-on AI engineering, experience deploying AI models in production, and expertise across Computer Vision, ML, GPU computing, and performance optimization.

Qualifications

• Hands-on AI/ML engineering and architecture experience.
• Experience deploying AI/ML models in production.
• Strong knowledge of Computer Vision, Deep Learning, and AI inference.
• Experience with AI orchestration, workflows, and distributed systems.
• Proficiency with Python; C++ preferred.

Responsibilities

• Lead the design and development of the AI intelligence and orchestration layer connecting perception, AI inference, decision-making, and robotic execution.
• Develop reliable AI workflows, state machines, and system logic for deterministic robotics operations.
• Integrate Computer Vision, ML/Deep Learning, and AI models into edge/on-premise robotics environments.
• Design APIs, microservices, and interfaces connecting AI, perception, robotics, and execution systems.
• Optimize GPU/compute performance, inference latency, throughput, and resource utilization for real-time workloads.
• Own production reliability including deployment, monitoring, logging, security, and continuous performance optimization.

Skills

AI/ML Engineering

Python

C++

AI Architecture

Computer Vision

Robotics AI

Deep Learning

GPU Computing

Performance Engineering

Security

Tools

REST APIs

gRPC

Docker

Linux

Job description

Careernet in Ajman, UAE, is seeking an AI Lead Engineer to architect and lead the intelligent software layer for an AI and robotics system. You will drive integration of AI models with perception, decision-making, and robotic execution in edge/on-premise environments.

The role requires hands-on AI engineering, experience deploying AI models in production, and expertise across Computer Vision, ML, GPU computing, and performance optimization.