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Internship Deep Learning information

What is an internship in deep learning?

An internship in deep learning is a temporary position, typically offered to students or recent graduates, where individuals gain practical experience working on projects involving neural networks, machine learning algorithms, and AI applications. Interns often assist with data preparation, model training, evaluation, and sometimes contribute to research or development of deep learning solutions. This role helps interns develop technical skills, gain exposure to real-world problems, and build a foundation for a career in artificial intelligence or related fields.

What is the difference between Internship Deep Learning vs Data Science Intern?

AspectInternship Deep LearningData Science Intern
Required SkillsMachine learning, neural networks, programming (Python, TensorFlow)Statistics, data analysis, programming (Python, R)
Work EnvironmentResearch-focused, AI/ML teams, tech companiesBusiness analytics, data analysis teams, various industries
Common Employer UsageTech firms, AI startups, research labsConsulting firms, tech companies, finance, healthcare

Internship Deep Learning roles focus on developing neural networks and AI models, often in research or tech environments. Data Science Internships involve analyzing data, creating insights, and supporting decision-making across diverse industries. Both internships require programming skills, but Deep Learning emphasizes AI-specific knowledge, while Data Science covers broader data analysis skills.

What types of projects or tasks can I expect to work on during a deep learning internship?

As a Deep Learning intern, you can typically expect to work on a variety of hands-on projects such as data preprocessing, model development, and performance evaluation. You may contribute to building and testing neural networks, experimenting with architectures like CNNs or RNNs, and assisting in preparing datasets for training. Collaboration with data scientists, engineers, and other interns is common, providing opportunities to learn best practices in model deployment and documentation. This role offers a valuable chance to gain practical experience in applying theoretical knowledge to real-world problems.

What are the key skills and qualifications needed to thrive in a deep learning internship, and why are they important?

To thrive in a Deep Learning Internship, you need a strong foundation in mathematics, programming (especially Python), and machine learning concepts, typically supported by ongoing or completed studies in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience using tools like Jupyter Notebook are highly valued. Strong problem-solving skills, curiosity, and effective communication help interns stand out when working on complex projects and collaborating with teams. These skills and qualities are crucial for efficiently developing, testing, and explaining deep learning models in a fast-evolving field.
What are the most commonly searched types of Deep Learning jobs in Illinois? The most popular types of Deep Learning jobs in Illinois are:
What are popular job titles related to Internship Deep Learning jobs in Illinois? For Internship Deep Learning jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Internship Deep Learning jobs in Illinois look for? The top searched job categories for Internship Deep Learning jobs in Illinois are:
Internship Deep Learning jobs near you
Infographic showing various Internship Deep Learning job openings in Illinois as of July 2026, with employment types broken down into 71% Full Time, 27% Part Time, and 2% Contract. Highlights an 73% Physical, 3% Hybrid, and 24% Remote job distribution.

Machine Learning Research Intern - Summer 2027 - Chicago

IMC

Chicago, IL

$300K/yr

Other

PTO

Re-posted 4 days ago

Job description

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
  • Proficiency in Python and modern machine learning frameworks such as PyTorch, Tensorflow, and/or JAX
  • Demonstrated research excellence through publications, preprints, research internships, or significant research projects; publications at venues such as NeurIPS, ICML, ICLR, or equivalent conferences are highly preferred
  • Must be able to start internship in-person 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: $300,000

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