2021-04041 - Machine Learning Engineering Intern

Contract type : Internship agreement

Level of qualifications required : Bachelor's degree or equivalent

Fonction : Internship Engineering

Level of experience : Recently graduated



DeepSearch is a new kind of collaborative, filter-based search engine that allows people to perform detailed search on the Internet efficiently, on any subject and from a single platform. We develop our own search engine technology powered by machine learning, which is able to filter any content from the internet according to the user's criteria.

The project, founded by Leo Cances (finishing his PhD in deep semi-supervised learning at the Institut de Recherche en Informatique de Toulouse) and Romain Zimmer (Télécom Paris 2019), is currently under development at Inria's Startup Studio in Paris.


Under the direct responsibility of the founding team, you will contribute to the generation of datasets and benchmarks of the different machine learning models we develop.

Main activities


  • Generate new datasets to train our models (mostly using web scraping, text processing, synthetic data generation using structured data and symbolic natural language processing)
  • Run ML experiments to benchmark the different machine learning models we developed



  • Strong Python skills
  • Experience in PyTorch, Tensorflow or any ML / DL framework
  • Experience in natural language processing
  • Good understanding of machine learning
  • Experience in linux operating system
  • Professional working English

Nice to have

  • Experience in Docker
  • Experience in any other programming language
  • Experience working from remote machines (and cloud instances)

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training