About the Job:
The company is a publicly funded research institute located in Abu Dhabi, UAE. It comprises a diverse community of leading scientists, engineers, mathematicians, and researchers dedicated to transforming challenges into pioneering research and technology prototypes that advance society.
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The Artificial Intelligence and Digital Science Research Centre (AIDRC) functions as the machine learning powerhouse of the company, collaborating closely with other research centers to harness the full potential of AI across various domains, including healthcare, cybersecurity, and advanced technology systems. The center focuses on ideation, design, and prototyping of next-generation systems that exhibit human-like intelligence.
Duties & Responsibilities:
- Design and develop agentic AI systems using Falcon and other foundation models for enterprise and government applications.
- Architect end-to-end Retrieval-Augmented Generation (RAG) pipelines encompassing data ingestion, chunking, embedding, hybrid retrieval, reranking, and grounded generation across diverse data sources.
- Optimize model serving and inference through frameworks like vLLM, focusing on batching, KV caching, quantization, and throughput tuning to meet performance targets.
- Lead prompt engineering, model selection, and lightweight fine-tuning to enhance application quality.
- Establish evaluation frameworks and benchmarks to measure the quality, safety, latency, and cost of AI systems, responding to results accordingly.
- Investigate and address AI failure modes (e.g., hallucination, retrieval gaps), implementing reusable solutions.
- Collaborate with full-stack engineers and product teams to translate business requirements into effective AI solutions, facilitating production deployment and iterative improvement.
- Contribute to internal AI frameworks and engineering best practices to accelerate future development across the center.
Job Specification:
- Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related discipline.
- 2 to 8 years of hands-on experience in building and deploying AI or machine learning systems in production environments.
- Proficiency in Python and experience with modern AI and ML libraries (e.g., PyTorch, Hugging Face Transformers).
- Proven expertise in agentic frameworks, production RAG systems, and model serving optimizations.
- Familiarity with containerization (Docker), CI/CD practices, and basic MLOps workflows.
- Strong communication skills; fluency in English is required (Arabic is a plus).
Additional Skills:
- Patents and publications in leading conferences (e.g., ICML, NeurIPS).
- Experience in deploying AI systems within regulated industries or Arabic-language contexts.
- Contributions to open-source AI projects.
