Performance Engineer Intern - Quantitative Trading & AI

ittihad medical centre; Chicago (IL); On-site; USD 180,000 - 220,000; Full time

Benefits offered by this job

Paid leave

Insurance

Discretionary bonus

Job summary

IMC Trading in Chicago is seeking highly driven interns to apply quantitative techniques and practical experimentation to our trading technology. You will perform quantitative research with large datasets, design strategies for liquidity and quoting, and develop AI agents and ETL pipelines in Python for ultra-low-latency trading.

Collaboration with Traders and with hardware/software engineers is essential. Ideal candidates are CS/Engineering students graduating between 2027 and 2028, with

Qualifications

• Current university student graduating between September 2027 - July 2028 pursuing CS/Engineering or related field.
• Proficiency in at least one programming language.
• Exceptional quantitative ability and analytical skills.
• Experience with statistical modeling, ML, or network technology is a plus.
• Strong communication and collaboration skills; cross-functional work with trading and engineering teams.
• Interest in Financial Markets; knowledge not required.
• Must be able to start internship on June 7, 2027.

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 AI agents, ETL pipelines and algorithms in Python to optimize IMC's ultra-low-latency trading strategies.
• Reverse-engineer and stress-test network and systems programming technologies to understand them better than manufacturers.
• Collaborate closely with Traders and with Hardware and Software Engineers who will implement your ideas.

Skills

Python

Quantitative ability

Statistical modeling

Machine learning

Networking

Education

CS/Engineering student

Job description

IMC Trading in Chicago is seeking highly driven interns to apply quantitative techniques and practical experimentation to our trading technology. You will perform quantitative research with large datasets, design strategies for liquidity and quoting, and develop AI agents and ETL pipelines in Python for ultra-low-latency trading.

Collaboration with Traders and with hardware/software engineers is essential. Ideal candidates are CS/Engineering students graduating between 2027 and 2028, with