Machine Learning Engineering Intern
International Machine Learning Olympiad
United StatesFresher3h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 1 year
- Must know
- Machine learningData structures & algorithmsDeep learningPythonscikit-learnPandas
- Work
- On-site in United States · internship
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning82%Python79%Data structures & algorithms29%Deep learning24%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 2, 2026 · still open
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About the Role
IMLO (International Machine Learning Olympiad) is a global initiative that provides a platform for students to showcase their technical skills, explore innovative ideas, and collaborate on cutting-edge AI challenges. This full-time remote Machine Learning Engineering Intern role focuses on supporting the design, implementation, and evaluation of machine learning models used in Olympiad-related projects and tools.
Key Responsibilities
- Collecting and preprocessing data.
- Experimenting with algorithms and deep learning architectures.
- Assisting in building reproducible ML pipelines.
- Implementing baseline models.
- Performing model tuning and performance analysis.
- Documenting experiments and results.
- Collaborating with mentors and other interns.
- Contributing to code reviews.
- Writing clear technical documentation.
- Supporting the development of educational materials and tools.
Requirements & Tech Stack
- Proficiency in a programming language commonly used in ML, such as Python.
- Familiarity with libraries like NumPy, pandas, and scikit-learn.
- Exposure to Deep Learning, including common neural network architectures and practical frameworks (e.g., TensorFlow, PyTorch).
Qualifications
- 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.
- 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.
- Currently pursuing or recently completed a degree in Computer Science, Data Science, Mathematics, or a related field.
- Clear written and verbal communication skills.
- Ability to work collaboratively in a remote, international team environment.
- Interest in educational initiatives, competitions, or community projects in AI and machine learning.