IMC Trading is seeking a Machine Learning Researcher 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.

Your Core 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 models and features
Oversee data acquisition, preprocessing, and feature engineering for structured and unstructured data sources
Ensure robust backtesting, validation, and model interpretability practices
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
Play critical role in implementing new trading ideas into production
Combine knowledge of systems, mathematical techniques and trading to identify system improvements

Your Skills and Experience:

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 high-frequency or low-latency environments
Strong programming skills in Python; proficiency in ML libraries such as PyTorch, TensorFlow, and/or high-performance libraries like Jax
Experience working with financial data, alpha generation, market microstructure, and/or alternative datasets.
Strong understanding of theoretical foundations of ML algorithms
Deep understanding of time series modeling, signal processing, and model evaluation
Prior people management experience preferred
Creative thinking skills and drive to solve challenging problems
Ability and desire to work in a collaborative team environment
Excellent written and verbal communication skills

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