About the Job: The company is a publicly funded research institute based in Abu Dhabi, United Arab Emirates. It houses a diverse community of leading scientists, engineers, mathematicians, and researchers from across the globe, aiming to transform problems into pioneering research and technology prototypes that advance society. This position is part of the company’s Robotics Research Center.
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Position Overview:
We are seeking a highly skilled Senior AI Engineer with deep expertise in Large Language Models (LLMs), Vision-Language Models (VLMs), and agentic model architectures. The ideal candidate will possess a strong foundation in both research and engineering, with hands-on experience in developing, fine-tuning, and deploying advanced AI systems. The role involves building scalable, production-ready AI applications, integrating multimodal reasoning, and advancing 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 low-latency inference systems for large models using frameworks like DeepSpeed, vLLM, TensorRT, or ONNX Runtime; implement distributed training and optimize deployment for edge devices, GPUs, and cloud platforms.
- Research & Innovation: Stay updated 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, with experience in fine-tuning and reinforcement learning techniques.
- Agentic Frameworks: Experience with frameworks like LangChain, LlamaIndex, AutoGPT, and Hugging Face.
- Development Tools & Libraries: Proficiency in core AI frameworks (PyTorch, TensorFlow) and supporting tools (Weaviate, Pinecone, FAISS).
- Programming Skills: Proficiency in Python and C++ for research and performance-critical components.
- Systems & Infrastructure: Knowledge of Docker, AI distributed training systems, and cloud platforms (AWS, GCP, Azure).
Qualifications:
- Master’s or PhD in Computer Science, AI/ML, Robotics, or a 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 or simulation environments.
- Publications in AI conferences.
At the company, we strive to help society overcome significant hurdles through a rigorous approach to scientific discovery and inquiry, fostering new breakthroughs in AI and other advanced technologies.
