AI Internship

About SiGMA Group

Founded in 2014 and headquartered in Malta, SiGMA Group is a global organisation
operating across iGaming, emerging technologies, affiliate marketing, events, and media.

With international teams operating across multiple markets, SiGMA delivers large-scale global events, digital platforms, content products, and internal technology solutions. AI Engineer

About the Internship

We are looking for an AI Engineering Intern to join the AI Department and learn how modern AI products are designed, built, tested, and deployed in a real business environment.

This internship is designed for a student, recent graduate, or self-taught developer who is interested in artificial intelligence and wants practical experience working alongside an AI engineering team.You do not need to be an experienced AI engineer.

The goal of the internship is to give you exposure to real projects while helping you develop practical skills in areas such as Python, large language models, prompt engineering, AI agents, RAG, APIs, automation, testing, and responsible AI.

What You Will Learn

• Large Language Models such as GPT, Claude, Gemini and open-source models

• Prompt engineering and structured prompting

• AI agents and agentic workflows

• Retrieval-Augmented Generation (RAG)

• Vector databases and embeddings

• APIs and integrations

• Python development

• Model testing and evaluation

• AI automation workflows

• Data preparation and basic data pipelines

• Git and collaborative development

• AI monitoring and observability

• Responsible AI and AI governance

• Moving AI ideas from prototype to working products

What You Will Do

• Work alongside AI engineers on active AI projects

• Build small AI prototypes and proof-of-concepts

• Experiment with prompts and different AI models

• Help test AI responses for quality, accuracy, and consistency

• Assist with simple RAG pipelines and document-based AI systems

• Build small Python scripts and API integrations

• Help create and test simple AI agents and workflows
• Prepare datasets and documents for AI experiments

• Research new AI tools, models, and frameworks
• Help test internal AI products before release
• Learn how AI systems are monitored after deployment