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Machine learning engineer – ai implementation & mlops

Neder-Over-Heembeek
Pauwels Consulting
Publiée le 30 avril
Description de l'offre

Overview

Scroll down to find the complete details of the job offer, including experience required and associated duties and tasks.

Our client, a dynamic organization in the public services sector, is seeking a specialist to drive the operationalization of machine learning solutions. The role focuses on building robust implementation, monitoring, and scalable ML pipelines within both cloud and on-premise environments.
Responsibilities

Design, build, and maintain production-ready machine learning models and end-to-end ML pipelines.
Process and analyze data from diverse sources to implement feature engineering and ensure data quality.
Translate experimental models into scalable services by integrating them into backend APIs and batch processes.
Establish MLOps practices, including CI/CD processes, version control, and model registry management.
Monitor model performance, latency, and drift to ensure long-term stability and reliability.
Collaborate with cross-functional teams to align technical implementations with the European AI Act.
Qualifications

3+ years of experience in data and machine learning development using

Python .
1+ years of experience with

Machine Learning libraries

such as

scikit-learn ,

PyTorch ,

Langraph ,

Ollama, and

LangChain .
1+ years of experience with

MLOps

practices, including

Azure DevOps ,

CI/CD, and experiment tracking.
1+ years of experience with

containerization

using

Docker

and deployment patterns.
1+ years of experience in

SQL

and data processing within production environments.
1+ years of experience with backend development using

C# ,

.NET, and

Blazor .
Experience with monitoring tools such as

DynaTrace ,

OpenTelemetry, and drift detection.
Strong analytical skills and a proactive, ownership-oriented mindset.
You are fluent in

Dutch

or

French

with a passive knowledge of the other language. xphnsxz
Nice to Haves

Practical knowledge of

Azure

cloud infrastructure.
Details

Start date:

ASAP
Duration:

project length
Work regime:

Full-time
Location:

Brussels
Working model:

Hybrid (2 days onsite per week)
Contract:

open to both permanent employees and freelancers

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