Machine Learning Engineer Intern

What you'll do

• Work closely with experienced ML engineers on the Onsite Recommendation Models team
• Build a unified multi-task recommendation model
• Dive deep into current recommendation systems such as Search-to-Product, Product Similarity, and Product Complementarity
• Explore state-of-the-art multi-task learning approaches for recommendation systems
• Extend and improve an existing two-tower deep learning model to support multiple recommendation tasks
• Design clear experimentation plans including model architectures, training objectives, evaluation metrics, and protocols
• Implement and train deep learning models using Python and PyTorch
• Run experiments, analyze results, and compare performance across tasks
• Contribute clean, scalable, production-ready code following best practices
• Document findings and share insights with the team at the end of the internship

Requirements

• Currently in the final year of a BSc or MSc in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field
• Strong foundation in machine learning and mathematics
• Comfortable coding in Python
• Hands-on experience or coursework in Deep Learning, ideally with PyTorch
• Enjoy working with data and experimenting with models
• Clear communication skills in English, both written and spoken
• Eager to learn, iterate, and take ownership of a technical project
• Available to start an on-site internship in Paris from June 2026
• Nice to have: Familiarity with recommendation systems
• Nice to have: Experience with large-scale or distributed training (e.g. GPUs, Ray)
• Nice to have: Exposure to Spark / PySpark

Tech stack

Benefits