Machine Learning Research Intern - Summer 2027 - Amsterdam

IMC B.V.; Amsterdam; On-site; EUR 16,740 - 23,436; Full time

Benefits offered by this job

Fully furnished corporateAccommodation

Catered meals

Job summary

IMC B.V. invites applications for a Machine Learning Internship spanning 10 weeks, split between Amsterdam and London. You will conduct hands-on ML research, work with large datasets, and contribute to research informing IMC's trading strategies across global markets.

Mentored by experienced researchers, you’ll design experiments and evaluate novel approaches in a fast-paced setting. The program emphasizes practical ML skills, classroom and on-desk training in quantitative trading, and

Qualifications

• Penultimate year student (graduating 2028).
• MSc in ML, Statistics, DL, probabilistic programming, or related quantitative field.
• Strong foundation in statistics and ML with demonstrable research in ML/DL or similar.
• Proficiency in Python and PyTorch.
• Desirable publications in journals on DL or time-series modeling.

Responsibilities

• Conduct hands-on research to design, develop, and apply ML algorithms with support to explore and innovate.
• Analyze large-scale datasets, develop predictive models, and evaluate novel approaches to market problems.
• Develop research skills through hands-on projects, mentorship, and feedback from researchers.
• Enhance understanding of quantitative trading through classroom-based instruction in options theory and market making.

Skills

Python

PyTorch

Machine Learning

Deep Learning

Statistics

Probabilistic Programming

Research

Education

MSc in Machine Learning/Statistics/Deep Learning/Probabilistic Programming or related field

Job description

Machine Learning Internship

Our Machine Learning Internship is designed for curious, ambitious researchers who want to apply machine learning to complex, real-world problems. Over 10 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 begin with a week of engaging, classroom‑based learning in the proprietary trading landscape, then 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. Split between our Amsterdam headquarters and time at our London office, the program also gives you the chance to broaden your network across IMC's regions.

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. You'll receive comprehensive support from dedicated internship trainers and a one‑on‑one mentor to guide you in your work and professional development. We offer a highly competitive compensation package, including fully‑furnished corporate accommodation and catered meals. 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

• Currently in your penultimate year of study, graduating in 2028.
• A minimum of an MSc in Machine Learning, Statistics, Deep Learning, Probabilistic Programming, or a related quantitative field.
• Strong foundations in statistics and machine learning, with a demonstrated research track record in ML, deep learning, or another quantitative field.
• Proficiency in Python and core machine learning frameworks such as PyTorch.
• Desirable: publications in respected journals covering deep learning or time‑series modeling.
• No prior finance knowledge or experience required.
• Ability to start the internship on the last week of June 2027.