Deep Learning Research Intern - Summer 2027 - Chicago, New York

InternHunt; Chicago, Northern (IL, KY); Hybrid; USD 28,000 - 48,000; Full time

Benefits offered by this job

Discretionary bonus

Paid leave

Health insurance

Job summary

IMC is offering a 10-week Deep Learning Research Intern program in Chicago and New York. You'll work with researchers on real projects, access large datasets and modern training infrastructure, and gain hands-on experience turning research into results.

We seek students pursuing PhD/Master's/Bachelor's in CS or related fields graduating 2027-2028, with deep learning experience, Python proficiency, and strong communication.

Qualifications

• Student pursuing PhD, Master's or Bachelor’s in a quantitative field and graduating 2027-2028.
• Experience applying deep learning techniques.
• Publications at ML venues or open source contributions are a plus.
• Strong Python skills and experience with modern DL frameworks.

Responsibilities

• Collaborate with researchers on real projects to build or improve models with business impact.
• Explore representation learning, transformers, foundation models, generative AI, or RL.
• Develop research skills with mentorship and intern lead.
• Participate in professional development and cohort events.

Skills

Deep Learning

Python

Research Methods

Education

Bachelor's/Master's/PhD in CS/Math/Engineering

Tools

PyTorch

TensorFlow

JAX

Job description

Deep Learning Research Intern - Summer 2027 - Chicago, New York

New York, USA

2026-10-02

Role Description

Our 10-week internship is your chance to experience life as a Deep Learning Researcher at IMC. You'll have access to rich, large-scale datasets and modern training infrastructure, and see firsthand how rigorous research translates into real-world results. No prior financial industry experience is required; we are looking for scientific thinkers who are passionate about advancing deep learning research. We provide a highly competitive compensation package with accommodations included. The bar for talent at IMC is high, and interns who meet our performance expectations will have the opportunity to secure a full-time Graduate Deep Learning Researcher position at the end of the program. Where you go from here is up to you!

Your Core Responsibilities

• Team up with Deep Learning Researchers on real projects to build or improve models that have potential to impact our business
• Explore research areas such as representation learning, transformers, foundation models, generative AI, and reinforcement learning and other emerging deep learning techniques
• Develop your research skills with support and feedback from a dedicated mentor and intern lead
• Engage in professional development sessions aimed at helping you envision your future at IMC
• Attend events and social activities to get to know your cohort and current employees

Your Skills And Experience

• Current university student pursuing a PhD, Master’s or Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Engineering, or a related quantitative field, and graduating between September 2027 and July 2028
• Experience in applying deep learning techniques
• Publication records at leading ML venues (NeurIPS, ICML, ICLR) or contributions to open source research a plus
• Strong programming skills in Python and hands-on experience with at least one modern deep learning framework, such as PyTorch, JAX, or TensorFlow
• A creative problem-solver who is driven, resilient, and able to explain complex ideas clearly to both technical and non-technical audiences
• Must be able to start the internship in person on June 7, 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.

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.