Senior Deep Learning Researcher for Quantitative Trading AI

IMC; Chicago (IL); On-site; USD 250,000 - 300,000; Full time

Benefits offered by this job

Discretionary bonus

Paid leave and insurance

Job summary

IMC is seeking a Deep Learning Researcher to advance quantitative trading through state-of-the-art models and scalable infrastructure. You will join a team pioneering large-scale pre-training, predictive modeling, and representation learning to shape trading strategies and execution.

The ideal candidate has a PhD or Master's in a quantitative field, 3+ years of DL research, and a track record applying cutting-edge techniques to real-world markets.

Qualifications

• PhD or Master's degree in a quantitative field (CS/ML/AI/Math/Engineering).
• 3+ years of experience in deep learning research and large-scale ML systems.
• Expertise in transformers, sequence models, self-supervised and generative models.
• Experience with distributed training and large-scale pretraining.
• Strong Python skills and experience with PyTorch, JAX, TensorFlow.
• Ability to build scalable ML infrastructure and deployment systems.
• Strong communication and collaboration in research-driven environments.

Responsibilities

• Build and improve deep learning models to enhance trading performance across assets.
• Innovate in representation learning, transformers, foundation models, generative AI.
• Research, prototype, and evaluate novel architectures for market state prediction.
• Support large-scale data curation and multimodal learning from structured data.
• Partner with traders, researchers, and engineers to translate insights into scalable solutions.
• Stay at the forefront of DL developments and share research with the team.

Skills

Python

PyTorch

JAX

TensorFlow

Distributed computing

Large-scale pretraining

Education

MS/PhD in CS/ML

Job description

IMC is seeking a Deep Learning Researcher to advance quantitative trading through state-of-the-art models and scalable infrastructure. You will join a team pioneering large-scale pre-training, predictive modeling, and representation learning to shape trading strategies and execution.

The ideal candidate has a PhD or Master's in a quantitative field, 3+ years of DL research, and a track record applying cutting-edge techniques to real-world markets.