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SiGMA World

AI Intern

SiGMA World

. Work alongside AI engineers on active AI projects .

Posted 9/24/2026internshipRemote • MaltaEntry LevelWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates capabilities in building AI prototypes, testing AI models for quality and accuracy, and preparing datasets for AI experiments. Proficient in Python scripting and API integrations, with a strong interest in AI tools and frameworks.

Highest-signal resume keywords
Python ProgrammingAI PrototypingPrompt EngineeringAPI IntegrationData Preparation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
PythonAI ModelsPrompt EngineeringAI AgentsRAGAPIsAutomationTestingData PipelinesData Preparation
Soft Skills
CollaborationCuriosityAdaptability
Tools & Technologies
Vector DatabasesEmbeddingsGitAI MonitoringObservability
Industry Keywords
Artificial IntelligenceResponsible AIAI Governance

Tech Stack

Tools & technologies
Python

About the role

Key responsibilities & impact
  • Work alongside AI engineers on active AI projects
  • Build small AI prototypes and proof-of-concepts
  • Experiment with prompts and different AI models
  • 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
  • Create and test simple AI agents and workflows
  • Prepare datasets and documents for AI experiments
  • Research new AI tools, models, and frameworks
  • Test internal AI products before release
  • Learn how AI systems are monitored after deployment

Requirements

What you’ll need
  • Student, recent graduate, or self-taught developer interested in artificial intelligence
  • Interest in gaining practical experience alongside an AI engineering team
  • Experience or interest in Python, large language models, prompt engineering, AI agents, RAG, APIs, automation, testing, and responsible AI
  • Familiarity with or willingness to learn vector databases, embeddings, data preparation, basic data pipelines, Git, AI monitoring, observability, and AI governance
  • No prior professional AI engineering experience required