Machine Learning Engineer (H/F) - CDI - Paris
Since 2014, Wiremind has positioned itself as a tech company transforming the world of transport and events with a 360° approach combining UX, software, and AI.
Our expertise lies primarily in optimizing and distributing our clients' capacity. We work on various projects such as ticket forecasting and pricing, 3D optimization of air freight or scraping competitor prices. Our applications are the preferred tool of companies such as SNCF, United Airlines, Qatar Airways or even PSG to visualize, analyze and optimize their capacity.
Dynamic and ambitious, we strive to maintain our technical DNA which is the engine of our success. The company, profitable and self-financed since its creation 10 years ago, is mainly composed of engineers and experts and currently supports the growth of our business model based on "software-as-a-service" solutions.
Your missions 🚀
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
You’ll be joining a dedicated AI/ML squad within the Data Science team, designed to bring together all the key expertise needed to build robust and scalable ML systems. You'll work hand-in-hand with software engineers, data engineers and ML experts to develop, validate, and maintain production-grade ML pipelines.
As a Data Scientist, with support from a Lead Data Scientist, you will take part in the development and improvement of new features and algorithms for our SaaS applications, using a mixture of proven traditional model-based methods as well as recent breakthroughs in Deep Learning for regression problems.
In practice, even though there is no typical day, you can expect to:
- Develop, maintain, and propose improvements for our training framework via Argo + MLFlow
- Deploy and monitor of models in production
- Oversee implementations of new clients from the data analysis phase, modeling, deployment, and monitoring of the mode
- Develop analytics and AB testing tools to help us continuously improving our models
- share with the other members of the team through model reviews, technical guidance, and best practices sharing
Technical stack:
- Backend: Python 3.11+ with SQLAlchemy
- Orchestration: Argo workflows over an auto-scaled Kubernetes cluster
- Datastores: Druid and postgresql
- Common ML libraries/tools: TensorFlow/Keras, LightGBM, XGBooost, Pandas, Dask, Dash, Jupyter notebooks
- Model versioning and registry tool: Mlflow
- Gitlab / Kubernetes for CI/CD
- Prometheus/Grafana and Kibana for operations
Your profile 🔍
- You have at least 1 or 2 years of experience working in Data Science, Applied Mathematics, Computer Science or similar fiel
- You have worked on at least one deep learning framework such as tensorflow or pytorch
- You have a pragmatic approach to ML where testing and frequent deliveries of small incremental gains supported by validation / alerting processes to avoid regression is preferred to a long tunneled research process
- You're passionate about addressing business challenges through innovative technological solutions
- You are committed to maintaining high-quality standards in all aspects of your work
- Experience modelling time series and/or price elasticity is a plus
Our benefits 🤌
En nous rejoignant, tu intégreras :
- Une startup autofinancée avec une forte identité technique ! 🧬
- De magnifiques bureaux de 700 m² au cœur de Paris (Bd Poissonnière) ✨
- Une rémunération attractive et indexée sur la performance 💪
- Une équipe bienveillante et stimulante qui encourage le développement des compétences à travers la prise d'initiative et l'autonomie
- Un environnement d'apprentissage avec des possibilités d’évolution 🧑💻
Tu bénéficieras également :
- De formations à la demande💡
- D’une politique hybride : 2 jours de télétravail par semaine et la possibilité de travailler ponctuellement depuis l’étranger 💻
- D’une belle culture d’entreprise (afterworks mensuels, réunions régulières sur la technologie et les produits, séminaires annuels hors site, team-buildings…)
- D’un budget annuel pour ton équipement informatique
- D’un partenariat avec le réseau de crèches inter-entreprises People & Baby pour faciliter l’accueil de tes enfants de 0 à 3 ans 🐣
Our recruitment process 🤞
- Un screening interview avec Anne-Laure, notre Sénior Talent Manager
- Un entretien avec Ali, Lead ML Engineer et Hiring Manager
- Un test technique ou une étude de cas à préparer
- Un entretien dans nos locaux pour discuter de ton test technique
- Un culture fit interview avec Charles, notre CTO et Co-fondateur
Wiremind is committed to equal opportunity, diversity, and equity. We encourage all qualified candidates to apply to our job openings.
- Département
- DATA
- Role
- ML Engineering
- Locations
- Paris
- Remote status
- Hybrid
About Wiremind
Since 2014, Wiremind has transformed transport and events with a 360° approach, integrating UX, software, and AI.
We excel in optimizing and marketing our clients' capacity, handling projects like ticket forecasting, pricing, 3D air freight optimization, and competitor price scraping. Our tools are trusted by companies like SNCF, United Airlines, Qatar Airways, and PSG for visualizing, analyzing, and optimizing capacity.
Dynamic and ambitious, we maintain our technical DNA, driving our success. Profitable and self-financed since inception, Wiremind consists mostly of engineers and experts, supporting our SaaS-based business model.
Already working at Wiremind?
Let’s recruit together and find your next colleague.