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Financial Services, Proprietary Trading, FinTech

Quant Performance Engineer Intern - Summer 2027

Chicago, ILOnsiteInternshipJunior / Entry-levelPosted 2 months agoVisa sponsorship available

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Required skills

  • Python
  • quantitative techniques
  • practical experimentation
  • large datasets
  • exchange microstructure
  • AI agents
  • ETL pipelines
  • algorithms
  • ultra-low-latency trading strategies
  • Traders

Nice to have

  • statistical modeling
  • machine learning
  • network technology

Role summary

IMC is seeking driven interns for Summer 2027 to apply quantitative techniques to electronic trading technology. Responsibilities include performing quantitative research on large datasets, designing strategies for exchange microstructure, developing AI agents and ETL pipelines in Python for ultra-low-latency trading, and reverse-engineering network/systems programming technologies. Interns will collaborate with Traders and Engineers. Requirements include current university student status (graduating Sept 2027-July 2028) in CS/Engineering, proficiency in at least one programming language, exceptional quantitative and analytical skills, and a competitive drive. Experience with statistical modeling, machine learning, or network technology is a plus. Strong communication and collaboration skills are essential. Interest in financial markets is not required.

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

    • 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.

    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

    #LI-DNP

    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.

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