CONTEXT
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:
With the acceleration of our growth,, the team is now entering a scaling phase where we will face the challenge to stay agile in terms of innovation while supporting and monitoring closely the in-production algorithms. To address this issue, we are starting to organize the work around Kubeflow (https://www.kubeflow.org/): a ML ops tool empowering data scientists to focus on high-added value tasks by maintaining a common framework and re-usable/ factorized components for all team members.
In this context, Wiremind is now looking for a senior ML engineer capable of making necessary evolution on this existing framework and processes while developing and maintaining scalable ML pipelines.
WHAT YOU WILL DO
In a team shaped to have all profiles necessary to constitute an autonomous departement (devops, software eng., data eng., IA, Operational research), you will be responsible for :
TECHNICAL STACK:
Python 3.7+
Kubeflow over an auto-scaled kubernetes cluster for orchestration
Druid as datastore
Common ML librairies (tensorflow, lgbm, pandas, dash…)
Gitlab for continuous delivery
WHAT IS IMPORTANT TO US
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