Quant Performance Engineer Intern - Summer 2027
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Before you apply
Salary$200k
LocationChicago, United States
Work modeon-site
Typeinternship
SeniorityEntry
DepartmentDevelopment (Group)
Company size1,001–5,000 people
PostedAug 27, 2026 · 2mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Current university student graduating between September 2027 - July 2028 pursuing a degree in Computer Science, Engineering, or a related technology field
Proficiency in at least one programming language
Exceptional quantitative ability and analytical skills
Highly motivated to compete—and win—in one of the world’s most competitive markets
Strong communication and collaboration skills, with a desire to work cross-functionally across trading and engineering teams
Interest in the Financial Markets; previous knowledge is NOT required
Experience with statistical modeling, machine learning, or network technology is a plus
Must be able to start internship on June 7, 2027
Skills
Python
LLM
Benefits
Health insurance
Paid leave
About the role
Technology is at the heart of modern electronic trading. IMC is seeking highly driven interns to apply quantitative techniques and practical experimentation to the technology used by exchanges, connectivity providers, and our own systems.
Your Core Responsibilities:
•
Perform quantitative research with large datasets to understand exchange technology.
•
Design novel strategies to optimize IMC’s liquidity taking and quoting strategies for exchange microstructure.
•
Develop ETL pipelines and algorithms in Python to optimize IMC’s ultra-low-latency trading strategies
•
Explore novel uses of frontier LLMs to accelerate data and research tasks
•
Reverse-engineer and stress-test network and systems programming technologies in order to understand them better than the manufacturers.
•
Collaborate closely with Traders and with the Hardware and Software Engineers who will implement your ideas.
Your Skills and Experience:
•
Current university student graduating between September 2027 - July 2028 that is pursuing a degree in Computer Science, Engineering, or a related technology field.
•
Proficiency in at least one programming language is required.
•
Exceptional quantitative ability and analytical skills.
•
Highly motivated to compete—and win—in one of the world’s most competitive markets.
•
Experience with statistical modeling, machine learning, or network technology is a plus.
•
Strong communication and collaboration skills, with a desire to work cross-functionally across trading and engineering teams.
•
Interest in the Financial Markets; previous knowledge is NOT required
•
Must be able to start internship on June 7, 2027
Hiring process
You may submit one application per role each year. We strongly encourage you to focus on applying to a single role that best matches your skills and interests. Though you may apply to multiple roles, please note that each application will be evaluated based on the specific criteria established for that particular role. If you have already applied for this position during the current recruitment season and were not selected, you may reapply when the next recruitment season begins in 2027.
Benefits
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.
Base Salary: $200,000
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.