Data Scientist – ML Engineer

HumanInTech; Brussel Hoofdstad; Hybride; EUR 70 000 - 110 000; Plein temps

Résumé du poste

HumanInTech is seeking a skilled AI/Data Science professional to join a three-month assignment in Brussels. You will participate in the design and development of AI and data science solutions, deploying models in production and maintaining ML pipelines in on-premise and hybrid environments.

A strong MLOps background and experience with Docker, Kubernetes and Kubeflow are essential. You hold a Master’s or PhD in CS/AI with at least three years of data science experience.

Qualifications

• Master's degree or doctorate in computer science, AI or equivalent.
• Minimum of three years of experience in data science, MLOps and machine learning.
• Experience deploying AI solutions on-premise and on cloud platforms (Azure, AWS, GCP).
• Experience with ML pipelines, Kubeflow, MLflow and SageMaker.
• Strong knowledge of SQL and NoSQL databases (PostgreSQL, MySQL, Milvus, Neo4J).
• Experience with Docker, Kubernetes and orchestration tools (Kubeflow).
• Experience with data storage solutions (data lakes, data warehouses, object storage).
• Fluent in English and at least one Dutch or French.

Responsabilités

• Participate in design and development of AI and data science solutions.
• Develop ML pipelines and monitor/maintain them.
• Deploy ML models in production, primarily on-premise.
• Implement best practices in programming and ML within projects.
• Stay updated with MLOps trends and technologies.
• Design end-to-end ML systems considering scalability, maintenance, and hardware constraints.
• Work with large structured and unstructured datasets.

Connaissances

Python programming

ML engineering

Data analysis

Team collaboration

Problem solving

Formation

Master's degree or PhD in CS/AI or equivalent

Outils

Docker

Kubernetes

Kubeflow

MLflow

SageMaker

PostgreSQL

MySQL

Neo4j

Milvus

SQL/NoSQL

Hugging Face

PyTorch

TensorFlow

scikit-learn

OpenCV

vLLM

Description du poste

What you will do

You will participate directly in the design and development of AI and data science solutions to meet operational and tactical needs. Your responsibilities include:

• Developing machine learning pipelines and ensuring their monitoring and maintenance
• Deploying AI models into production, primarily in on-premise environments
• Implementing best standards in programming and machine learning within your projects
• Conducting technology watch to stay current with the latest developments in MLOps and machine learning
• Designing end-to-end ML systems taking into account scalability, robustness, maintenance and hardware constraints
• Working with large structured and unstructured datasets

What we are looking for

You hold a master's degree or doctorate in computer science, AI or equivalent, with a minimum of three years of experience in data science, MLOps and machine learning.

Technical expertise:

• On-premise and cloud development: expertise in developing and deploying AI solutions on-premise and on cloud platforms (Azure, AWS, GCP)
• Three or more years of industry experience in ML, MLOps and big data with a focus on large-scale deployment
• Theoretical background and practical expertise in machine learning and deep learning
• Strong knowledge of relational and non-relational databases (SQL and NoSQL), including PostgreSQL, MySQL, Milvus, Neo4J
• Demonstrable experience in deploying ML models and expertise in MLOps
• Experience with containerisation and deployment using Docker and Kubernetes, as well as orchestration tools like Kubeflow
• Mastery of ML pipelines (Kubeflow, MLflow, SageMaker)
• Mastery of CI/CD implementation for ML models and associated code
• Experience with different data storage solutions (data lakes, data warehouses, object storage such as S3)

Hard skills:

• Databases: MySQL, PostgreSQL, Neo4j, Milvus
• AI frameworks: Hugging Face, MLflow, PyTorch, TensorFlow, scikit-learn, OpenCV, vLLM
• Programming languages: Python (R is a plus)
• Orchestration and containerisation: Docker, Kubernetes, Kubeflow
• Software engineering: uv, ruff, black
• Cloud platforms: Azure, AWS
• Versioning (code and models): MLflow, Git, GitHub, GitLab

Soft skills:

• Ability to bring people together: aligning diverse profiles around a common objective
• Sense of priorities: identifying critical tasks, maintaining a long‑term vision, and reorganising work in response to unexpected developments
• Clear and spontaneous communication: transmitting the right message at the right time and level, explaining technical concepts to non‑technical stakeholders
• Problem‑solving and analytical thinking: approaching problems in a structured way, identifying root causes and proposing pragmatic solutions
• Collaboration: working constructively with all stakeholders, fostering exchanges and co‑construction of solutions
• Attention to detail: focusing on technical, functional and organisational aspects of projects, ensuring code quality, model robustness and compliance with standards
• Rigour: systematically applying best practices and methodologies, documenting work precisely, and ensuring consistent project follow‑up

An awareness of security, ethical and legal aspects is appreciated.

The setting

This is a three‑month assignment starting in October 2026, based in Brussels with a hybrid working arrangement.

You must have active knowledge of English and at least one of the two national languages (Dutch or French).

You can join us for this assignment as a freelancer or as an employee of HumanInTech. Same role, same team. If you join as an employee, your employment continues beyond this assignment. When it ends, we’ll work together to find your next assignment.

Location: Brussels, hybrid

Employer / contracting party: HumanInTech

Applications close (Brussels time): October 1, 2026 at 2:00 AM

Engagement: Freelance or employed by HumanInTech

Working hours: Full-time

Experience: 3–5 years or more

Education: Master's or more

Published: September 2026