AI Engineer

Technology Innovation Institute; United Arab Emirates; On-site; AED 120,000 - 180,000; Full time

Job summary

A leading AI research institute in the United Arab Emirates is seeking an AI Engineer to develop and optimize advanced AI systems, including large language models and vision-language models. The ideal candidate must hold a Master’s or PhD in a relevant field and possess substantial hands-on experience in deploying AI solutions at scale. This role emphasizes innovation and collaboration, allowing you to push the boundaries of autonomous intelligent agents and multimodal reasoning.

Qualifications

• Hands-on experience developing, fine-tuning, and deploying advanced AI systems.
• Proven track record of productionizing AI systems at scale.
• Strong knowledge of reinforcement learning and alignment techniques.

Responsibilities

• Design, train, fine-tune, and optimize LLMs and VLMs.
• Build scalable, low-latency inference systems for large models.
• Stay up to date with advancements in LLMs and autonomous agents.

Skills

LLMs expertise

VLMs expertise

DeepSpeed

Python

C++

Cloud platforms knowledge

Education

Master’s or PhD in Computer Science, AI/ML, or related field

Tools

PyTorch

TensorFlow

Hugging Face

Docker

Job description

Position Overview

We are seeking a highly skilled AI Engineer with deep expertise in Large Language Models (LLMs), Vision-Language Models (VLMs), and agentic model architectures. The ideal candidate will have a strong foundation in both research and engineering, with hands‑on experience developing, fine‑tuning, and deploying advanced AI systems. You will contribute to building scalable, production‑ready AI applications, integrating multimodal reasoning, and pushing the boundaries of autonomous intelligent agents.

Key Responsibilities

• LLM/VLM Development & Integration: Design, train, fine‑tune, and optimize LLMs and VLMs for real‑world scenarios.
• Agentic AI Systems: Develop and orchestrate autonomous agent frameworks capable of multi‑step reasoning, planning, and tool use.
• Engineering & Deployment: Build scalable, low‑latency inference systems for large models using frameworks like DeepSpeed, vLLM, TensorRT, or ONNX Runtime. Implement distributed training, model parallelism, and efficient inference pipelines; also optimize deployment for edge devices, GPUs, and cloud‑based platforms.
• Research & Innovation: Stay up to date with the latest advancements in LLMs, multimodal models, and autonomous agents.

Core Competencies

AI/ML Expertise

• Strong understanding of LLMs, VLMs, transformers, and multimodal architectures.
• Experience with fine‑tuning, LoRA/QLoRA, quantization, distillation, and evaluation.
• Knoledge of neurosymbolic methodologi
• Knowledge of reinforcement learning (RLHF, RLAIF) and alignment techniques.

Agentic Frameworks

• Experience with frameworks such as LangChain, LlamaIndex, AutoGPT, CrewAI, OpenAI Agents, Hugging Face Transformers/Agents.
• Ability to design reasoning loops, memory systems, and multi‑agent coordination.

Development Tools & Libraries

• Core AI frameworks: PyTorch, TensorFlow, Hugging Face, OpenAI APIs, DeepSpeed, vLLM.
• Supporting tools: Weaviate, Pinecone, FAISS, Milvus (vector databases), Redis, Kafka.
• Evaluation/monitoring: Weights & Biases, MLflow, TensorBoard, Evals frameworks.

Programming Skills

• Python – for AI research, prototyping, and deployment pipelines.
• C++ – for performance‑critical components, model inference optimization, and system integration.

Systems & Infrastructure

• Proficiency with Docker, and AI distributed training systems.
• Strong knowledge of CUDA, GPU optimization, and high‑performance computing.
• Familiarity with cloud platforms (AWS, GCP, Azure) and edge deployment strategies.

Qualifications

• Master’s, or PhD in Computer Science, AI/ML, Robotics, or related field.
• Proven track record of hands‑on work with LLMs, VLMs, or agentic frameworks.
• Experience in productionizing AI systems at scale.
• Excellent communication and collaboration skills.

Preferred (Nice‑to‑Have)

• Experience with reinforcement learning
• Background in robotics, simulation environments, or embodied AI.
• Publications in AI conference

At TII, we help society to overcome its biggest hurdles through a rigorous approach to scientific discovery and inquiry, using state‑of‑the‑art facilities and collaboration with leading international institutions. Our rigorous discovery and inquiry‑based approach helps to forge new and disruptive breakthroughs in AI, advanced materials, autonomous robotics, cryptography, digital security, directed energy, quantum computing and secure systems.