Deep Learning Researcher

About the Role

IMC Trading is in search of an accomplished Deep Learning Researcher who has demonstrated success in developing and applying advanced deep learning methodologies to solve intricate real-world challenges. The successful applicant will join a pioneering team at the forefront of deep learning advancements and infrastructure development, including large-scale model pre-training, predictive analytics, and representation learning, all aimed at enhancing trading operations.

The role offers a unique opportunity to intersect AI research and quantitative trading by leading projects involving modern neural network architectures, self-supervised learning, foundation models, generative AI, reinforcement learning, and custom deep learning methods tailored for financial markets.

Responsibilities

• Design and refine sophisticated deep learning models to boost trading effectiveness across various asset classes.
• Innovate in dynamic domains such as representation learning, transformer models, foundation architectures, generative AI, and reinforcement learning.
• Investigate, prototype, and assess new neural network designs and training techniques relevant to market state forecasting, signal creation, trade execution optimization, and portfolio management.
• Contribute to large-scale data preparation, feature engineering, self-supervised learning, and multimodal learning integrating structured and unstructured data.
• Collaborate closely with quantitative traders, researchers, and engineers to convert market knowledge and business goals into practical deep learning systems.
• Maintain awareness of the latest academic and commercial developments in deep learning, disseminating pertinent research findings within the team.

Candidate Qualifications

• PhD or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Engineering, or related quantitative disciplines.
• At least three years of experience engaged in deep learning research and the development of large-scale machine learning solutions.
• Demonstrated mastery of contemporary deep learning frameworks including transformers, sequence models, representation learning, self-supervised techniques, and generative models.
• Deep comprehension of the theoretical bases of deep learning encompassing optimization methods, statistical learning theory, and neural network training dynamics.
• Expertise with training and deploying extensive models in distributed computing settings; experience in large-scale pretraining is strongly preferred.
• Proficiency in Python programming and hands-on experience with cutting-edge deep learning toolkits such as PyTorch, JAX, TensorFlow, and their ecosystems.
• Experience developing scalable machine learning infrastructure, experimentation environments, and deployment pipelines.
• Excellent communication skills capable of presenting complex technical ideas clearly to both technical specialists and broader audiences.
• Proven ability to excel in a highly collaborative, research-intensive environment.

About IMC

IMC is a research-led trading company that leverages quantitative modeling, machine learning, and engineering to shape modern market operations. Established in 1989, IMC provides liquidity across global trading venues, ensuring optimal value and risk management for investors. Utilizing proprietary technology and capital, IMC creates innovative systems and algorithms that operate worldwide. The firm's culture blends rapid innovation, advanced infrastructure, and real-time feedback, turning analytical insights into competitive advantages.