Sasol: Youth Development Internship Programme 2024 / 2025

Join our dynamic team as an Intern: AI Engineer, where you'll be immersed in the exciting world of machine learning, deep learning, and data-driven insights. We’re looking for candidates with a passion for AI technologies who are keen to learn and grow in a fast-paced environment.

As an intern, you’ll play a key role in developing AI models, experimenting with various AI techniques, and supporting the deployment of AI solutions. You will receive training that will develop your AI engineering skills, along with exposure to the latest AI tools and frameworks.

Responsibilities:

• Collaborate with data scientists and software engineers to design, build, and fine-tune AI models.
• Explore machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
• Conduct exploratory data analysis to derive insights and inform model development.
• Collect, clean, and pre-process data to ensure it's ready for use in AI models.
• Implement AI algorithms using Python libraries such as PyTorch, TensorFlow, scikit-learn, and others.
• Optimize AI models for accuracy, performance, and scalability.
• Learn how to deploy AI models in cloud environments (e.g., AWS, Azure, Google Cloud).
• Work with the engineering team to integrate AI models into production systems.
• Experiment with new AI techniques and contribute to ongoing AI projects.
• Stay up-to-date with the latest advancements in AI research and technologies.
• Use data visualization tools to present AI model outcomes and insights to stakeholders.
• Assist in creating reports that demonstrate the impact of AI on business objectives.

Requirements:

Bachelor's degree in:

• Computer Science
• Data Science
• Mathematics
• Statistics
• Engineering
• Artificial Intelligence
• Operations Research

NB. An Honours/MSc/MEng will be an advantage

Skills and Competencies:

• Programming: Proficiency in Python and familiarity with AI libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Machine Learning: Knowledge of key machine learning algorithms and techniques.
• Data Processing: Experience with data cleaning, preparation, and feature engineering.
• Problem Solving: Ability to approach problems creatively and analytically.
• Communication: Strong written and verbal communication skills for explaining technical concepts