Machine Learning Engineer Intern

Who you are

• You are pursuing a BS/MS in Computer Science, Computer Engineering, or quantitative science fields, a PhD is a plus
• You have implementation experience with high-level languages, such as Python, Scala, Java, C/C++
• You have experience in building or improving CI/CD pipelines and in machine learning
• You have knowledge and experience with container tools such as Docker
• You are familiar with MLOps frameworks (Azure ML Studio, MLFlow, Kubeflow…)
• You are fluent in English, speaking French is a plus
• Please note: to apply, you must be able to complete 6 months of internship and have an agreement issued by your school/university

What the job involves

• Want to join the world's No. 2 in wines & spirits and work among convivial teams? Pernod Ricard is looking for a Machine Learning /MLOps Intern for 6 months from July 2026. You will be based at the Island, our office in central Paris (Saint Lazare Train Station, Paris 8)
• In this role, you’ll have the chance to roll up your sleeves to scale our data science models. Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative
• You will contribute to the MLOps process implementation to maintain ML models in production
• You will collaborate with the team to deploy or improve scalable and efficient pipelines using best MLOps practices
• You will collaborate with the team on production quality service development with Unit & Integration testing, CI/CD & devOps for these services
• You will maintain and contribute to the API serving our web application
• You will identify new opportunities to improve go-to-production, MLOps processes and improve end-to-end experiences
• You will apply software development practices and standards to enhance and ensure the code quality of our applications
• You will maintain an active role in every part of the software development life cycle
• You will actively contribute to Data platform community

The application process

• Target Hire Date: 2027-04-01
• Target End Date: 2027-06-30