AI Researcher

About the Role

As an AI Researcher at Vatic Labs in Abu Dhabi, you will research and develop innovative AI-driven quantitative trading strategies. You will explore vast amounts of market and alternative data, inventing and applying a new generation of state-of-the-art technologies that are inspired by large language models, deep neural networks, transformers, and advanced prompt engineering methods to discover and capitalize on trading opportunities.

The nature of the problems we work on is challenging, hence we hire some of the world's top AI talent to develop novel AI methods and trading strategies. Our team of talented researchers and technologists has been recognized as leaders in their field. Our distinguished researchers have been widely cited for their publications in top-tier, peer-reviewed scientific journals. We are passionate about hiring the best and the brightest, empowering them with the tools and mentorship needed to be successful. Our environment is highly collaborative and open, sharing AI and trading expertise across team members and fostering innovation and growth.

Requirements

• Earned or will earn a Master’s or Ph.D. in a quantitative field, such as Computer Science, Electrical and Computer Engineering, Applied Math, Statistics, Quantitative Finance, Cognitive Science, Physics or another field of science.
• Experience analyzing large data sets with rigorous statistical and ML/AI approaches, including classification, clustering, regression (linear and nonlinear), optimization, signal processing, filtering and smoothing, time-series analysis, hidden Markov models, high-dimensional data analysis, vector quantization, decision tree methods, EM methods, Bayesian methods, variational inference methods, and neural networks.
• Demonstration of deep knowledge of large language models and deep neural networks for practical applications (e.g. NLP, vision, speech, signal processing, scientific computing, finance, etc). Finance applications preferred but not necessary.
• Ability to generate impactful research in academic or professional pursuits.
• Advanced understanding and experience of practical programming languages and software tools for data analysis and ML/AI applications, such as Python, C++, PyTorch, Tensorflow, etc.
• Interest and enthusiasm for learning about financial markets (previous experience not required).