At Wiremind, the Data Science team is responsible for the development, monitoring and evolution of all ML-powered forecasting and optimization algorithms in use in our Revenue Management systems. Our algorithms are divided in 2 parts:

• A modelling of the unconstrained demand using ML models (e.g. deep learning, boosted trees) trained on historical data in the form of time-series

• Constrained optimizations problems solved using linear programming techniques

The team is now entering a scaling phase where we will face the challenge to stay agile in terms of innovation while supporting and closely monitoring deployed algorithms.

In this context, Wiremind is now looking for an experienced ML engineer, capable of working with a rich codebase in order to make the additions necessary to our framework and processes, all the while developing and maintaining scalable ML pipelines.

Technical stack:

• Python 3.11+

• Argo over an auto-scaled kubernetes cluster for orchestration

• Druid as datastore

• Common ML libraries: tensorflow, lgbm, xgboost, pandas, dask, dash, mlflow

• Gitlab for continuous delivery

• Strong computer science background in python, with a keen interest for code quality and best practices (unit testing, pep8, typing)

• Knowledge about at least one major deep learning framework, e.g. tensorflow, pytorch

• A pragmatic, prod-oriented approach to ML: frequent, incremental gains beat a grand quest for perfection.

• At least 2 years of experience as a data scientist / ML engineer

WHAT WOULD BE A PLUS

• A first experience in a pricing-related domain

• A first, short introduction call with our Talent Acquisition Manager and/or a member of the Tech Team

• A short technical test to be prepared before next interview will be sent ; you will be invited at our Paris offices for the case study restitution, and meet the team

Wiremind is committed to equal opportunities, diversity and fairness. We encourage all candidates with the necessary experience to apply for our vacancies.