Machine Learning Engineering Intern

IMLO (International Machine Learning Olympiad) is hiring a Machine Learning Engineering Intern to support the design, implementation, and evaluation of machine learning models for Olympiad-related projects and tools. The intern will work on data preparation, model experimentation and tuning, reproducible ML pipelines, documentation, and educational resources in collaboration with mentors and other interns.

Responsibilities:

• Day-to-day responsibilities include collecting and preprocessing data, experimenting with algorithms and deep learning architectures, and assisting in building reproducible ML pipelines
• The intern will help implement baseline models, perform model tuning and performance analysis, and document experiments and results for internal and external stakeholders
• The role also involves collaborating with mentors and other interns, contributing to code reviews, writing clear technical documentation, and supporting the development of educational materials and tools used by Olympiad participants

Requirements:

• Strong foundation in Computer Science, including data structures, algorithms, and software engineering principles
• Knowledge of Machine Learning concepts such as supervised and unsupervised learning, model evaluation, and feature engineering
• Exposure to Deep Learning, including common neural network architectures and practical frameworks (e.g., TensorFlow, PyTorch)
• Understanding of Statistics, including probability, distributions, hypothesis testing, and basic data analysis
• Ability to design and analyze Algorithms for efficient data processing and model training
• Proficiency in a programming language commonly used in ML (such as Python) and familiarity with libraries like NumPy, pandas, and scikit-learn
• Currently pursuing or recently completed a degree in Computer Science, Data Science, Mathematics, or a related field
• Clear written and verbal communication skills and the ability to work collaboratively in a remote, international team environment
• Interest in educational initiatives, competitions, or community projects in AI and machine learning