About IMC
IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. It provides liquidity across trading venues and builds proprietary systems and algorithms that operate across global markets.
Responsibilities
•Build and improve deep learning models to enhance trading performance across multiple asset classes, under the guidance of senior researchers
•Contribute to research in representation learning, transformers, foundation models, generative AI, reinforcement learning, and other emerging deep learning techniques
•Support large-scale data curation, feature representation, and self-supervised and multimodal learning from structured and unstructured datasets
•Contribute to shared training infrastructure and deployment pipelines
•Track academic and industry developments in deep learning and share relevant research with the team
Requirements
•Currently in the final year of study, graduating in 2027
•At least an MSc in Machine Learning, Statistics, Deep Learning, Probabilistic Programming, or a related quantitative field
•Demonstrated experience in deep learning research or applied machine learning
•PhD candidates: research contributions published at leading ML venues such as NeurIPS, ICML, or ICLR
•Bachelor's and Master's candidates: research experience through thesis work, open-source contributions, or projects
•Hands-on experience with modern deep learning architectures, including transformers, sequence models, representation learning, self-supervised learning, or generative models
•Solid understanding of deep learning theory, optimization, statistical learning, and neural network training dynamics
•Strong Python programming skills and hands-on experience with at least one modern deep learning framework, such as PyTorch, JAX, or TensorFlow
•Strong communication skills and ability to explain technical ideas to technical and non-technical audiences
•Prior financial industry experience is not required
Conditions
No conditions specified in the posting.
