Data & AI Technology Intern

About the role

The Data & AI Technology team at Accenture helps organizations become data-driven and AI-first, designing, building and operating modern data platforms and AI solutions. This full-time internship starts in February 2027 and is based in Brussels. You will join a cross-functional team of engineers, data scientists and functional experts, learning through hands-on assignments, guidance and regular feedback.

Key responsibilities

• Contribute to the development and testing of data, machine learning and AI solutions under the guidance of experienced team members.
• Assist with data collection, preprocessing, cleaning, validation and feature engineering.
• Help explore and document business use cases, user needs and functional requirements.
• Support the creation, testing and monitoring of machine learning pipelines, prototypes or proof-of-concept solutions.
• Collaborate with technical and business colleagues and take part in team discussions and working sessions.
• Document experiments, findings, solution designs and lessons learned.
• Assist with workflow automation and gain exposure to version control, CI/CD and containerization.
• Help define or track simple indicators to assess the impact of AI solutions.
• Research emerging Data & AI technologies and share insights with the team.
• Take part in Agile ceremonies, code reviews and knowledge-sharing sessions.

Required profile

• Currently enrolled in a bachelor's or master's programme in computer science, AI, data science, engineering, business or a related field.
• Eligible to complete an internship as part of your academic programme and able to provide the required internship agreement through your institution.
• Fluency in English and either French or Dutch.
• Curiosity, structured problem-solving, attention to detail and good communication skills.

Required skills

• Basic knowledge of Python and an interest in data, analytics, machine learning or Generative AI.
• Nice to have: academic project experience, basic Git, exposure to Azure, AWS or Google Cloud, and awareness of Agile, CI/CD, Docker, Kubernetes, MLflow or Airflow.