AI/NLP/ML Engineer

TalentTrade
Ixelles, Belgium
2 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
€ 155K

Job location

Ixelles, Belgium

Tech stack

Artificial Intelligence
Databases
Elasticsearch
Python
PostgreSQL
Machine Learning
MongoDB
NLTK
Oracle Applications
TensorFlow
SQL Databases
PyTorch
Delivery Pipeline
Large Language Models
Deep Learning
Model Validation
Pandas
Scikit Learn
Information Technology
HuggingFace
Machine Learning Operations
Spacy

Job description

Long term contract (up to 2.5 years)

  • Remote-first with occasional onsite in Brussels.
  • Works well if you're based within a short flight of Brussels (for example Kraków or similar locations).

You're already building with AI. Now you want to push further, working with LLMs, real-world data, and models that actually get used. This role puts you at the centre of advanced NLP and ML development, where you'll shape how intelligent systems are designed, tested, and scaled across products.

What changes for you You'll move beyond isolated models into end-to-end AI systems used in production. You'll work with LLMs and RAG frameworks to solve real language problems. You'll influence architecture, not just model outputs. You'll test, refine, and improve models with measurable impact. What you'll be doing

  • Design and optimise NLP and ML models using modern approaches including LLMs and RAG.
  • Build pipelines for tokenisation, classification, clustering, and entity recognition.
  • Fine-tune transformer models for domain-specific use cases.
  • Develop scalable Python-based solutions using libraries like Hugging Face, SpaCy, and NLTK.
  • Experiment, test, and improve model performance using structured evaluation methods.
  • Contribute to ML architecture, including model serving and GPU optimisation.
  • Collaborate with teams to integrate AI into live products.

Requirements

  • EU27 citizenship.
  • Master's degree in Computer Science, Data Science, Statistics, or similar.
  • Strong experience in Machine Learning and NLP, including hands-on work with LLMs.

You'll likely bring experience in

  • Python and ML libraries such as Pandas, SpaCy, NLTK, Hugging Face.
  • Deep learning frameworks like TensorFlow or PyTorch.
  • SQL and databases such as PostgreSQL, Oracle, MongoDB, or Elasticsearch.
  • A/B testing, experimentation, and model evaluation.
  • Building scalable ML systems and handling bias in models.

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