Senior AI Scientist, Large Language Models & Applied Machine Learning

Senior AI Scientist

Location: Abu Dhabi, UAE

A distinguished, macro-oriented single family office founded by a leading systematic investor is building a next-generation AI platform to augment investment research, portfolio construction and decision-making.

We are seeking a Senior AI Scientist to lead advanced model development across large language models and applied machine learning within a highly research-driven environment.

Relocation package will be provided for overseas candidates.

Role Overview

You will work at the intersection of quantitative research and frontier AI, developing and optimising large-scale models that power agentic systems and internal investment intelligence platforms. This is a hands-on role combining deep ML research capability with practical production impact.

Key Responsibilities

• Lead end-to-end LLM development including pre-training, fine-tuning (SFT), alignment and RL-based optimisation
• Design advanced data curation, synthetic data generation and evaluation pipelines
• Improve model reasoning, factual grounding and robustness through structured experimentation
• Collaborate with AI Engineers to translate research models into scalable production systems
• Develop internal benchmarking frameworks and evaluation metrics for model performance, reliability and safety

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• Contribute to long-term AI strategy within a capital markets environment

Requirements

• Advanced degree (Master’s or PhD) in Machine Learning, Computer Science, Mathematics, Physics or related field
• Strong hands-on experience with PyTorch and modern ML frameworks
• Experience with LLM training, fine-tuning, alignment techniques (SFT, RLHF or similar)
• Deep understanding of model architectures, optimisation techniques and scaling laws

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• Strong Python capability and experimental rigour
• Experience from leading AI labs, top-tier tech companies or research-intensive environments preferred

Ideal Profile

• Background in building or advancing foundation models or domain-adapted LLM systems
• Experience improving reasoning quality, context handling and robustness in complex environments
• Comfortable operating in a lean, high-calibre research team with high ownership