MACHINE LEARNING RESEARCH LEAD

Imc International Bv • Chicago, IL

250d

About The Position

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying state-of-the-art machine learning to solve challenging trading problems. This role will drive the development of a centralized ML environment to be used across all areas of trading at IMC. The ideal candidate will have experience working with other researchers, traders, and engineers to build and continuously improve a research platform to drive innovation via ML. We firmly believe that success for research-driven efforts lies in bringing together skills in ML, statistics and trading intuition as well as a problem-solving mindset and pragmatism. This is an opportunity to dive deep into feature engineering and focus on applying a wide range of ML models as well as to perform research on building custom models.

Requirements

• PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field
• 4+ years of experience building applied ML models; previous experience in trading environment preferred
• Proven expertise in developing and deploying predictive models in low-latency environments
• Strong programming skills in Python; proficiency in ML libraries such as PyTorch, TensorFlow, and/or high-performance libraries like Jax
• Strong understanding of theoretical foundations of state-of-the-art ML models
• Prior people management experience preferred
• Ability and desire to work in a collaborative team environment
• Excellent written and verbal communication skills

Responsibilities

• Lead the design, development, and deployment of machine learning models to enhance trading performance across various asset classes
• Research, test and prototype new algorithmic ideas; deploy advanced ML techniques applicable to market prediction, signal generation, and portfolio optimization
• Collaborate with quantitative traders, researchers and developers to translate market insights into data-driven features and models
• Oversee data acquisition, preprocessing, and feature engineering for structured and unstructured data sources
• Mentor junior researchers and contribute to a culture of research excellence and experimentation
• Drive strategic decisions on model architecture, experimentation pipelines, and infrastructure for scalable research

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Repair and Maintenance
• Education Level: Ph.D. or professional degree