Internship: Graduate AI Engineer

We are excited to announce our Graduate AI Engineer Internship Programme – a 6-month internship designed for recent graduates interested in computer vision (CV), natural language processing (NLP), and machine learning (ML). In this role, you will report to the Lead AI Engineer and Manager of the AI Division, receive dedicated mentorship and formal training, and contribute to real-world AI-driven projects across all three domains. The role is based in Cape Town, with a hybrid working mode (40/60 in office/remote split).

KEY RESPONSIBILITIES

• Collaborate with the data science team to assist in the development, evaluation, and monitoring of CV, NLP, and ML projects, gradually taking on greater ownership as your skills grow.
• Explore and analyse large-scale unstructured image datasets using advanced image processing and deep learning techniques (e.g., object detection, segmentation).
• Process and model unstructured text corpora and structured data (e.g., CSV, database tables) using NLP pipelines, LLM fine-tuning, and traditional ML algorithms.
• Support deployment and optimisation of models on both cloud and edge devices, tailoring solutions to meet customer requirements and resource constraints.
• Conduct feature engineering, data preprocessing, and model benchmarking for classification, regression, clustering, and anomaly-detection tasks.
• Maintain version control (Git), CI/CD workflows, and comprehensive documentation for reproducible model pipelines.
• Participate in problem-solving sessions, contribute innovative ideas, and present findings to technical and non-technical stakeholders.

KEY SKILLS, KNOWLEDGE, AND QUALIFICATIONS

• Recent graduates with a BSc (or higher) in Computer Science, Data Science, Machine Learning, or a related field.
• Strong foundation in Python and essential libraries (numpy, pandas, matplotlib).
• Familiarity with ML/deep learning frameworks: TensorFlow, Keras, PyTorch, scikit-learn.
• Exposure to CV libraries (OpenCV, scikit-image, PIL) OR NLP frameworks (HuggingFace Transformers, spaCy, NLTK).
• Understanding of core ML concepts: supervised/unsupervised learning, neural networks, evaluation metrics.
• Basic knowledge of version control systems (Git) and willingness to learn CI/CD best practices.
• Good verbal and written communication skills for effective teamwork and presentations.

PREFERRED CHARACTERISTICS (NOT MANDATORY TO HAVE ALL

• Interest or experience in cloud platforms (AWS, Azure, GCP) and edge computing (NVIDIA Jetson, Raspberry Pi).
• Familiarity with containerisation and orchestration tools (Docker, Kubernetes).
• Knowledge of performance, scalability, and production-hardening of ML systems.
• Exposure to Agile methodologies (Scrum, Kanban) and collaborative development workflows.
• A proactive mindset, strong curiosity, and passion for continuous learning in AI.

ABOUT US

Aizatron is an emerging technology fusion company that is looking to build local skills amongst youth in South Africa and are keen to employ a candidate that shows enthusiasm, willingness to work hard and learn on the job. Previous work experience in computer vision and/or deep learning for object detection and tracking along with semantic or instance segmentation either in academic or industrial domain design will be an advantage.

Our team places a strong emphasis on cultivating a work-life balance culture in the spaces we operate within. We are a professional and comfortable working environment focused primarily on learning, growth, knowledge sharing, teamwork, and collaboration.

Aizatron is committed to its diversity amongst the company and teams within, we welcome the applications from all members of society regardless of sex, disability, sexual orientation, race, religion or belief.

We are dedicated to developing, supporting and mentoring our team members to continuously improve their skills and effectiveness by offering training courses with our key partners such as AWS, with a view to develop better-rounded professionals in the environment we operate within.

Excited to be the newest member of our team, e-mail your CV and certified qualification documents to

by no later than Friday, 24 October 2025. We can't wait to meet you