Intern ML

Company Description PPStack is a global EdTech brand focused on reimagining the future of education by equipping students, professionals, and organizations with skills needed for the digital era. The company combines artificial intelligence, technology, and innovative teaching methods to make learning smarter, faster, and more impactful. PPStack’s mission is to bridge the gap between education and industry through future-ready skills, digital empowerment, and career transformation opportunities. Its ecosystem includes AI-powered learning platforms, crash courses, corporate training, career coaching, digital branding, technology consulting, and research in learning technologies, all designed to help learners worldwide build meaningful, future-focused careers.
Role Description The Intern ML role at PPStack is a full-time remote position focused on supporting the design, development, and evaluation of machine learning solutions that power the company’s educational and career products. Day-to-day tasks may include data collection and preprocessing, implementing and experimenting with ML models, conducting literature reviews on AI and ML methods, and assisting in model performance evaluation and optimization. The intern will collaborate with engineering, product, and content teams to integrate ML features into learning platforms, analytics dashboards, and AI-powered tools. Responsibilities also include documenting experiments, preparing reports or presentations, and contributing to prototypes and proof-of-concept projects aligned with PPStack’s EdTech offerings.
Qualifications
Foundational knowledge of machine learning and data science concepts, including supervised and unsupervised learning, model evaluation, and basic statistics.
Experience with programming for ML (e.g., Python) and familiarity with common ML libraries or frameworks (e.g., NumPy, pandas, scikit-learn, TensorFlow, or PyTorch).
Ability to work with datasets, including data cleaning, feature engineering, and exploratory data analysis using tools such as Jupyter or similar environments.
Understanding of AI/ML applications in domains such as education, personalized learning, recommender systems, or analytics is beneficial.
Strong problem-solving, analytical thinking, and willingness to learn new tools, techniques, and frameworks quickly.
Clear written and verbal communication skills, with the ability to document experiments and collaborate effectively in a remote, cross-functional environment.
Currently pursuing or recently completed a degree in Computer Science, Data Science, AI/ML, Engineering, or a related discipline, or equivalent practical experience.
Familiarity with version control (e.g., Git) and basic software engineering practices is a plus.

Work arrangement
No