MARGO
6 days ago
Machine Learning Engineer – IA Practice MARGO
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Company information
- Company
- MARGO
- Location
- Paris Germany
- Posted
- 6 days ago
Job description
Who are we?
At MARGO, our consultants work on what truly matters: complex projects that combine intellectual challenge and real business impact.
This is why we support the biggest players in finance, industry, and tech on their most strategic Data Science, Machine Learning, and Artificial Intelligence projects.
Why join the AI Practice?
You will evolve within a team mentored by Hamza Bouanani, AI Practice Manager at MARGO, also Lead Data Scientist at BNP Paribas.
Working alongside him means joining a team of passionate experts, being challenged technically and methodologically, and contributing to high-impact projects for clients.
Your missions
We are looking for a Machine Learning Engineer to join our teams and be at the heart of our clients' Data strategy (Industry, Finance, Energy). Your main objective will be to industrialize Machine Learning algorithms and guarantee their life cycle in production.
You will be involved in three major technical areas:
1. Industrialization & Deployment (Model Serving)
- Transformation of research models (Proof of Concept) into robust, tested, and optimized production code.
- Development of high-performance APIs (FastAPI, Flask) to expose models to business applications.
- Containerization of solutions (Docker) and orchestration on clusters (Kubernetes) to ensure scalability and high availability.
2. MLOps Architecture & Automation
- Design and maintenance of CI/CD pipelines dedicated to Machine Learning ( automatic retraining, model validation).
- Implementation and management of data flow orchestration tools (Airflow, Kubeflow, Dagster).
- Management of data and model versioning (DVC, MLflow) to ensure experiment reproducibility.
3. Performance & Optimization
- Optimization of response times (latency) and the use of computing resources (CPU/GPU).
- Code refactoring to adhere to Software Craftsmanship standards (Clean Code, TDD).
- Management of Feature Stores to centralize and serve real-time calculated variables.
Your role will also include:
Advanced Monitoring: Implementation of probes to detect "Data Drift" or "Model Drift" and trigger proactive alerts.
Cross-functional Collaboration: Bridging the gap between Data Scientists (mathematics/modeling) and Data Engineers (infrastructure/data) to streamline production deployments.
Evangelism: Disseminating good software development practices within Data Science teams.
Profile sought
We are looking for a hybrid profile, at the intersection of Software Engineering and Data Science, capable of understanding the underlying mathematics while mastering IT production constraints.
- Education: Master's degree (engineering school, university) in Computer Science or Applied Mathematics.
- Core Technical Skills:
* Advanced mastery of Python and software best practices (Git, Unit/Integration Tests, Packaging).
* Solid experience with Cloud platforms (AWS, Azure, or GCP) and IaC (Terraform is a plus).
* Mastery of the MLOps ecosystem: MLflow, Kubeflow, Docker, Kubernetes.
- Data Knowledge: Good understanding of ML libraries (Scikit-learn, Pandas) and Deep Learning (TensorFlow, PyTorch) to optimize Data Scientists' code.
- Experience: You have significant experience in deploying ML models in production (batch or real-time).
- Mindset:
* Absolute rigor on code quality and automation.
* Enjoyment of solving complex architectural problems.
* Ability to work in heterogeneous technical environments.
What we offer
- Ambitious and varied missions, always selected for their added value;
- Close support from recognized experts;
- A community of passionate engineers, with workshops, conferences, and regular exchanges;
- A culture of technical excellence, knowledge sharing, and continuous development.
What's next?
First interview: Discuss with a recruiter and a business developer
Technical interview: Showcase your skills and receive feedback
Motivation interview: Meet a member of the executive committee
COMMITMENT TO INCLUSION
MARGO is committed to offering equal opportunities to all; we cultivate an inclusive work environment that values diversity.
Required skills
- docker
- packaging
- ci/cd
- ai
- python
- aws
- kubernetes
- pytorch
- software engineering
- git
- cloud
- airflow
- gcp
- azure
- terraform
- data science
- architecture
- fastapi
- tensorflow
- tdd
- dagster
- flask
- iac
- machine learning engineer
- integration tests
- unit tests
- mlflow
- mlops
- pandas
- ia
- scikit-learn
- kubeflow
- batch
- clean code
- real-time
- feature stores
- dvc
- model drift
- data drift
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