Since 2014, Wiremind has positioned itself as a technical company transforming the world of transport and events with a 360° approach combining UX, software, and AI.

Our expertise lies primarily in optimizing and marketing 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 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 will be joining a team shaped to have all profiles necessary to constitute an autonomous department (DevOps, software and data engineering, data science, AIML, operational research) and will work on a modern MLOps stack composed of Druid (data warehouse), argo-workflow (pipelines orchestrator), MLFlow (models & experiments tracking) and in-house python packages to glue these components together.

As an MLOps Engineer, you will be responsible for:

• Maintaining the existing MLOps platform used by our ML engineers to train and deploy models

• Improving the MLOps platform with new features such as model automatic retraining

• Deploying ML models in production in a safe, scalable and maintainable way

• Exchanging on a daily basis with our ML team to share ideas about how to improve our solution and provide technical support on the stack

• Tackling technical debt, propose new solutions and challenge architecture decisions to keep on improving the code base

Technical stack

• Backend: Python 3.11+ with SQLAlchemy, Remoulade, FastAPI

• Kubernetes for infrastructure

• Orchestration: Argo workflows over an auto-scaled Kubernetes cluster

• Database: Postgresql, Redis, Druid

• Model versioning and registry tool: MLFlow

• Common ML libraries/tools: pytorch, LightGBM, pandas, Dask, Dash, Jupyter

• Gitlab for continuous delivery

• Prometheus/Grafana and Kibana for operations

Your profile 🔍

• You have an Engineering degree and 3 to 5 years experience in either MLOps, Software engineering, Data engineering or a related field

• You are proficient in a backend programming language and have experience collaborating on large code bases

• You are rigorous and committed to deliver high quality, thoroughly tested code

• You show interest for Data science & ML applications and are familiar with ML projects lifecyles

• You excel at debugging across multiple layers of architecture

• You are fluent in both French and English

Our benefits 🤌

By joining us, you will integrate:

• A self-financed startup with a strong technical identity! 🧬

• Beautiful 700 m² offices in the heart of Paris (Bd Poissonnière) ✨

• Attractive remuneration indexed on performance 💪

• A caring and stimulating team that encourages skills development through initiative and autonomy

• A learning environment with opportunities for evolution 🧑‍💻

You will also benefit from:

• Training on demand💡

• A hybrid policy: 2 days of remote work per week and the possibility to work occasionally from abroad 💻

• A great company culture (monthly afterworks, regular meetings on technology and products, annual off-site seminars, team-building…)

• An annual budget for your IT equipment

• A partnership with the People & Baby network of inter-company nurseries to help with childcare for children aged 0 to 3 🐣

Our Recruitment Process 🤞

1. A screening interview with Anne-Laure (Lead Talent Acquisition)

2. A Screening interview with Constant (Head of Data)

3. A technical test or case study to be prepared

4. An interview at our offices to discuss your technical test or case study and meet with Constant and a member of the team

Wiremind is committed to equality of opportunity, diversity, and fairness. We encourage all candidates with the necessary experience to apply for our job offers.