Machine Learning Intern

Company Description Weskill is an innovative online training platform focused on upskilling undergraduate students through practical, hands-on learning. The organization designs programs that close the gap between academic curricula and real-world corporate expectations. By emphasizing industry-relevant skills and project-based work, Weskill prepares learners to contribute effectively from day one in professional environments. Graduates are equipped for roles at high-growth startups and leading multinational companies, positioning them for a strong career trajectory. Weskill fosters a supportive, learning-centered culture that encourages curiosity and continuous improvement.
Role Description The Machine Learning Intern will support the design, development, and evaluation of machine learning models for educational and training applications. Day-to-day responsibilities include collecting and preprocessing data, experimenting with algorithms, implementing deep learning architectures, and analyzing model performance. The intern will collaborate with mentors to document experiments, refine approaches based on feedback, and contribute to internal tools, prototypes, or course materials. This is an internship role and is fully remote, allowing the intern to work flexibly while meeting deadlines, participating in online meetings, and sharing progress regularly. The role provides exposure to real-world machine learning workflows, best practices, and collaborative software development.
Qualifications
Strong foundation in Computer Science, including data structures, Algorithms, and programming fundamentals.
Knowledge of core Machine Learning concepts, such as supervised and unsupervised learning, model evaluation, and feature engineering.
Understanding of Deep Learning principles and experience with neural network frameworks or libraries.
Background in Statistics, including probability, statistical inference, and basic data analysis techniques.
Familiarity with Python or another high-level language commonly used in ML, along with libraries such as NumPy, pandas, scikit-learn, or PyTorch/TensorFlow.
Currently pursuing or recently completed an undergraduate degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
Ability to learn independently, manage time effectively in a remote environment, and communicate clearly in written and spoken English.
Interest in education, online learning platforms, and applying ML to real-world problems is highly beneficial.

Work arrangement
Yes