Junior AI Consultant: Build Real AI Solutions & Grow

Netherlands; Belgique; Sur place; EUR 32 000 - 42 000; Plein temps

Avantages offerts par ce poste

Company car not included

Fuel card not specified

Meal vouchers not specified

Bonus

Training and development

Résumé du poste

Datashift in Belgium is seeking a Junior AI Consultant starting September 2027 to build real-life AI solutions. You will translate business questions into AI use cases with consultants and clients, and prepare data for modelling using Python and SQL.

You will build and evaluate models from classic ML to LLMs, work with Data Engineers to integrate models into dashboards or APIs, and help monitor model quality through MLOps practices and A/B tests.

Qualifications

• Master in Engineering, CS, AI or applied maths.
• Solid Python skills and understanding of ML concepts.
• Familiar with SQL and data modelling; NoSQL/data warehouses a plus.
• Cloud tooling such as Azure and popular ML libraries.

Responsabilités

• Translate business questions into concrete AI use cases with consultants and clients.
• Explore, clean and prepare data for modelling (Python, SQL, notebooks).
• Build and evaluate AI models (classic ML to LLMs and CV).
• Collaborate with Data Engineers and BI to deploy models into data products, dashboards or APIs.
• Help monitor and improve model quality, robustness and fairness in production (MLOps, A/B tests).
• Contribute to demos, PoCs and internal AI knowledge sharing.

Connaissances

Python

SQL

Clear communication

Team player

Formation

Master in Engineering

Master in Computer Science

Master in Artificial Intelligence

Master in Applied Mathematics

Outils

Azure

scikit-learn

PyTorch

Hugging Face

LLM / RAG frameworks

Docker

Git

Description du poste

Datashift in Belgium is seeking a Junior AI Consultant starting September 2027 to build real-life AI solutions. You will translate business questions into AI use cases with consultants and clients, and prepare data for modelling using Python and SQL.

You will build and evaluate models from classic ML to LLMs, work with Data Engineers to integrate models into dashboards or APIs, and help monitor model quality through MLOps practices and A/B tests.