Machine Learning Research Intern - Summer 2027 - Chicago

IMC is recruiting for Machine Learning Research Intern - Summer 2027 - Chicago in Chicago, United States. This listing was last seen on the firm's own job board on August 22, 2026.

Options market making with a technology-first culture and a lighter maths bar than its Amsterdam neighbour.

What sets IMC apart: Traders and engineers hired into the same programme and trained together. Lower mental maths bar than Optiver, higher weight on logic puzzles. Strong campus presence in the Netherlands, Chicago, and India.

Related preparation: Quantitative Researcher (QR) Career Roadmap, Machine Learning Quant Career Roadmap, Quant Strategist (Desk Quant) Career Roadmap, Quant Data Scientist (Alternative Data) Roadmap, Quant Research Ops (MLOps) Roadmap and Financial Data Scientist Career Roadmap.

The role, as IMC describes it, published on July 1, 2026 and reproduced from their job board:

Our Machine Learning Internship is designed for curious, ambitious researchers who want to apply machine learning to complex, real-world problems. Over 10–12 weeks, you'll work alongside experienced researchers and mentors to develop models, analyze large-scale datasets, and contribute to research that informs IMC's trading strategies across global equities, futures, and options markets. You'll gain hands-on experience designing experiments, evaluating novel approaches, and tackling challenging problems in a collaborative, fast-paced environment where your work can have real-world impact.

Throughout the program, you'll deepen your understanding of quantitative trading through a combination of classroom and on desk training, while benefiting from professional development and networking opportunities. We offer a highly competitive compensation package, including travel and accommodation. High-performing interns may be considered for a full-time Graduate Researcher position upon graduation.

YOUR CORE RESPONSIBILITIES:

Conduct hands-on research to design, develop, and apply original machine learning algorithms, with the support to explore and innovate.

Analyze large-scale datasets, develop predictive models, and evaluate novel approaches to complex market problems

Develop your research skills through hands-on project work, mentorship, and regular feedback from experienced researchers

Enhance your understanding of quantitative trading through classroom-based instruction in options theory, market making, and related topics

YOUR SKILLS AND EXPERIENCE:

Pursuing a PhD in Machine Learning, Computer Science, Electrical Engineering, Mathematics, Statistics, Physics, or a related quantitative field and graduating between September 2027 – July 2028

Strong foundations in machine learning, probability, and statistics, with experience applying advanced ML techniques to solve challenging research or real-world problems

Demonstrated hands-on research experience in deep learning fundamentals such as neural network architectures, sequence modeling, training dynamics, or optimization