Machine Learning Researcher

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

Job summary

IMC Trading is a research-driven trading firm seeking quantitative researchers to apply state-of-the-art machine learning and deep learning to solve challenging trading problems. This role sits in a central ML research team that collaborates with trading teams to build models, systems, and research tooling.

The candidate will dive deep into feature engineering and alpha research, focusing on applying a wide range of ML models and building custom models for market prediction and portfolio

Qualifications

• PhD or Master’s in Engineering, Math, Statistics, Computer Science, or related quantitative field.
• 2+ years of experience building applied ML models; trading environment preferred.
• Proven expertise in developing and deploying predictive models.

Responsibilities

• Design and deploy machine learning models to enhance trading performance across asset classes.
• Research, test and prototype new algorithmic ideas; deploy advanced ML techniques for market prediction and portfolio optimization.
• Collaborate with traders, researchers, and developers to translate market insights into data-driven features and models.
• Manage data acquisition, preprocessing, and feature engineering for structured and unstructured data sources.

Skills

Python programming

ML model development

Collaborative research

Communication skills

Research publication

Education

PhD or MSc in Engineering/Math/Statistics/CS

Tools

PyTorch

TensorFlow

Jax

Job description

IMC Trading is seeking quantitative researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a central ML research team that collaborates across trading teams at IMC. The ideal candidate will have experience working with other researchers and engineers to build and continuously improve models, systems, and research tooling. 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 alpha research, and focus on applying a wide range of ML models as well as to perform research on building custom models.

Your Core Responsibilities:

• Design and deploy 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
• Manage data acquisition, preprocessing, and feature engineering for structured and unstructured data sources

Your Skills and Experience:

• PhD or Master’s in Engineering, Math, Statistics, Computer Science, or related quantitative field
• 2+ years of experience building applied ML models; previous experience in trading environment preferred
• Proven expertise in developing and deploying predictive models
• 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
• Strong publication track record at ICML, ICLR, NeurIPS, or equivalent
• Ability and desire to work in a collaborative team environment
• Excellent written and verbal communication skills

The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance.Please visit Benefits - US | IMC Trading for more comprehensive information.

Salary Range

$250,000 — $300,000 USD

About Us

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.