Technology Innovation Institute (TII) is a publicly funded research institute based in Abu Dhabi, United Arab Emirates. It is home to a diverse community of leading scientists, engineers, mathematicians, and researchers from across the globe, transforming problems and roadblocks into pioneering research and technology prototypes that help move society ahead. This role is part of TII’s Robotics Research Center.
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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 applications.
- 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.
- Knowledge of neurosymbolic methodologies and 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 conferences.
