AI Quantitative Researcher

Durlston Partners

Durlston Partners

AI Quantitative Researcher

Durlston Partners
Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates Full-timeFirst posted: 21 Sep 2026Last updated: 21 Sep 2026
Financial Services
Job Description

AI Quantitative ResearcherWe are working with a leading quantitative trading firm based in Abu Dhabi to find an AI Researcher to join their team. Our client applies cutting edge AI research to financial markets, combining rigorous quantitative methods with the latest advances in machine learning.You will research and develop AI-driven quantitative trading strategies, exploring vast amounts of market and alternative data. You'll invent and apply state of the art technologies inspired by large language models, agentic AI agents, deep neural networks, transformers, and advanced prompt engineering to discover and capitalize on trading opportunities. You'll join a team of top AI talent recognized as leaders in their field, widely cited in top-tier journals, working in a collaborative, flat environment.What you'll bring:Master's or Ph.D. in a quantitative field (Computer Science, EE, Applied Math, Statistics, Quantitative Finance, Physics, or similar).Experience with statistical and ML/AI methods: classification, clustering, regression, optimization, signal processing, time-series analysis, Bayesian methods, neural networks, and related techniques.Deep knowledge of large language models, agentic AI agents, and deep neural networks (NLP, vision, speech, finance, etc.).Experience designing or deploying autonomous/multi-agent AI systems is a plus.Track record of impactful research, academic or professional.Strong programming skills (Python, C++, PyTorch, TensorFlow).What's on offer:Flat structure with direct executive exposure, work closely with leadership from day one.Top tier compensation, reflecting the caliber of talent on the team.State of the art systems and infrastructure to support cutting-edge AI research.The opportunity to work at the frontier of AI, applying LLMs, agentic systems, and deep learning to real world financial markets.

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