Data Engineer / ML Engineer – Python, GCP & MLOps

Project overview

Mission Context

As part of the development and evolution of its Data & AI platform, our client is seeking a Data / ML Engineer consultant to strengthen its technical teams.

You will be involved in projects with a strong Data Science and Machine Learning dimension, particularly around personalization, recommendation, and intelligent data exploitation solutions.

Integrated into a multidisciplinary team composed of developers, Data Engineers, Data Scientists, and technical experts, you will contribute to the design, industrialization, and continuous improvement of Data & ML solutions deployed in a Cloud environment.

Your main missions

Technical skills sought

Data Engineering

Machine Learning & MLOps

Cloud & Infrastructure

Profile sought

Do you want to work on ambitious Data & AI projects with real industrialization and production deployment challenges? Don't hesitate to send us your application!

• Design and develop complete data pipelines: ingestion, transformation, structuring, and data provisioning.
• Develop and industrialize Machine Learning pipelines, from dataset preparation to model deployment and inference.
• Participate in the production deployment of Deep Learning models and solutions based on embedding architectures.
• Implement mechanisms for data quality control, testing, monitoring, and observability.
• Contribute to the design and evolution of Data and ML architectures on Google Cloud Platform.
• Participate in improving the performance, scalability, and reliability of existing processes.
• Be involved in the operational maintenance of pipelines and services, as well as incident resolution.
• Participate in the evolution of DataOps and MLOps practices, particularly in workflow orchestration and automation.
• Collaborate with various technical and business teams to propose solutions adapted to functional needs.
• Contribute to documentation, code reviews, and the dissemination of good engineering practices.
• Python
• BigQuery
• dbt and data quality testing tools (Elementary or equivalent)
• Apache Kafka and streaming architectures
• Data modeling and data pipeline design
• Terraform
• Strong command of Python applied to Machine Learning
• Knowledge of Deep Learning models and embedding-based architectures
• Design of ML pipelines: training, evaluation, deployment, and inference
• Industrialization of models for real-time use
• Orchestration and MLOps tools (ZenML or equivalent)
• Docker and Kubernetes
• Git
• Google Cloud Platform (GCP)
• Understanding of distributed architectures and cloud-native environments
• Automation and industrialization of deployments
• Significant experience in Data Engineering and/or ML Engineering.
• Good understanding of modern Data architectures and distributed systems.
• Mastery of the data lifecycle and the challenges of quality, governance, and observability.
• Ability to industrialize Machine Learning models and deploy them in production.
• Knowledge of streaming architectures and distributed processing.
• Sensitivity to issues of performance, scalability, and Cloud cost optimization.
• Autonomy, initiative, and ability to work in a team within a multidisciplinary technical environment.
• Professional English required; French appreciated.

Project details

• Start: 30/11/2026
• Duration: 2 ans
• Remote: hybrid
• Location: Lille, Hauts-de-France, FR
• Rate: 50-65 EUR/h
• Languages: French