Purpose of the job

• 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.

Key Accountabilities

As an Intern: AI Engineer, you’ll be involved in:

AI Model Development:

• 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.

Data Preparation and Analysis:

• Collect, clean, and pre-process data to ensure it’s ready for use in AI models.
• Conduct exploratory data analysis to derive insights and inform model development.

Algorithm Implementation:

• Implement AI algorithms using Python libraries such as PyTorch, TensorFlow, scikit-learn, and others.
• Optimize AI models for accuracy, performance, and scalability.

Automation and Deployment:

• Work with the engineering team to integrate AI models into production systems.
• Learn how to deploy AI models in cloud environments (e.g., AWS, Azure, Google Cloud).

AI Research and Experimentation:

• Stay up-to-date with the latest advancements in AI research and technologies.
• Experiment with new AI techniques and contribute to ongoing AI projects.

Visualization and Reporting:

• 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.

Skills

• 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

Wish List

• Experience with cloud platforms (AWS, Azure, or Google Cloud) for AI model deployment.
• Familiarity with big data tools (e.g., Hadoop, Spark).
• Experience with MLOps tools for automating the AI lifecycle.

Formal Education

Honours/MSc/MEng in:

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