Commodities – Machine Learning Engineer

Potential Locations: Miami FL, London UK

Citadel is one of the largest alternative investment managers in the commodities markets. Our investments are based on our deep understanding of commodity market fundamentals. We express our investment views through financial derivatives, physical supply and offtake, and financing.

Commodities have undergone an information revolution. From ship tracking to oil storage levels and crop yields, more data on supply, demand, storage, and transport is available than ever before. Commodity markets are more globally connected: natural gas markets impact fertilizer production, while agricultural markets impact gasoline production. Understanding these dynamics with the goal of delivering consistent investment returns presents a set of incredible opportunities and complex challenges. Our business brings together exceptional people to do just that. We combine specialist domain expertise with advanced modeling techniques to solve problems that others deem unsolvable.

We are often looking for strong Machine Learning Applied Scientists and Engineers to join our Commodities business. Such roles would involve solving various machine learning problems (statistical, computer-vision, NLP), conducting autonomous research, and implementing novel approaches with a commercial focus.

The roles would provide the opportunity to collaborate with multiple investment teams and improve our analytical processes by leveraging data and discovering new insights.

We are interested in candidates from across the experience spectrum, from recent graduates to experienced industry professionals.

If you are interested, please share your resume and we will contact you if and when there is an open opportunity that you may be qualified for.   

–          In depth knowledge of at least one machine learning branch (Generative modeling/Video Modeling/Representation learning/NLP+LLM/Reinforcement Learning)

–          Proven track record of leveraging deep learning by publishing at top AI conferences / outstanding commercial projects

–          Excellent Python coding

–          Demonstrated knowledge of machine learning programming frameworks, such as PyTorch, Jax and TensorFlow

–          Outstanding analysis, problem-solving skills, and tenacity to discover

–          Strong written and verbal communication skills on both technical and non-technical topics

–          Good knowledge of statistics

–          Willingness to work full time in-office due to role requirements

–          Industry experience of delivering end-to-end deep learning-based product

–          PhD / master’s degree

–          Large-scale distributed models training experience

–          Basic understanding of commodity and/or financial markets