AI Summary
Design and implement NLP and generative AI solutions for EU institutions. Deploy and maintain machine learning models, ensure data quality, and apply MLOps practices. Required expertise in Python, machine learning, and AI model lifecycle management.
Key Highlights
Develop and deploy NLP and LLM‑based AI applications for European institutions.
Implement MLOps pipelines for continuous integration, delivery, and monitoring of models.
Ensure data governance, bias mitigation, and compliance with AI regulations.
Key Responsibilities
Develop, train, and maintain machine learning models and software applications in NLP and AI, including large language models and generative AI.
Deploy generative AI models or integrate their APIs and Retrieval Augmented Generation (RAG) techniques.
Select features, build, and optimize classifiers using machine learning techniques.
Perform studies and developments to improve machine translation quality for specific language pairs.
Interact with data stewards and IT stakeholders to define data rules, ensure data quality, and mitigate bias in datasets and AI models.
Create automated anomaly detection systems and continuously track their performance.
Design and propose technical architecture for NLP/ML/AI solutions and coordinate implementation with engineering teams.
Assess data architecture against quality dimensions and recommend target‑state improvements.
Draft technical guidelines, documentation, and presentations for both technical and non‑technical audiences.
Implement MLOps practices to automate the ML lifecycle, including CI/CD, monitoring, and model retraining.
Stay abreast of the latest AI/ML research and pilot innovative solutions to maintain competitive advantage.
Technical Skills Required
Benefits & Perks
Hybrid work (Brussels office + remote)
Health and Life Insurance
Tech Visa support for non‑EU candidates
Nice to Have
Experience with cloud platforms for LLM solutions (e.g., AWS Bedrock, Azure AI Studio)
Familiarity with AI agent orchestration frameworks such as LangChain or Semantic Kernel
Knowledge of AI Act compliance and AI risk mitigation
Job Description
Do you live in Portugal and would like to work for European institutions in Brussels? Then this opportunity is for you!
We are hiring a AI/ML Engineer for the EU Institution in Brussels, Belgium:
Nature of the tasks
- Develop, train, and maintain machine learning models and software applications in the fields of Natural Language Processing (NLP) and Artificial Intelligence (AI), including the application of Large Language Models (LLMs) and generative AI for specific use cases.
- Deploy generative AI models or integrate their APIs, and Retrieval Augmented Generation (RAG) techniques,
- Select features, build and optimize classifiers using machine learning techniques.
- Perform studies and developments aiming at improving the quality of machine translation (MT) engines for each installed language pair, addressing the specific needs of customers of the service concerning MT quality and contributing to a general strategy for the systematic evaluation and long-term improvement of MT quality.
- Interact with data stewards and other IT stakeholders to define the data rules.
- Define data controls and implement strategies to ensure data quality, integrity, and the detection and mitigation of bias in datasets and AI models.
- Create automated anomaly detection systems and constant tracking of its performance.
- Perform processing, cleansing, and verifying the integrity of data used for analysis.
- Design and propose the technical architecture for NLP/ML/AI solutions, coordinating its implementation with engineering teams while adhering to data management principles (master data management, metadata).
- Assess data architecture against quality dimensions (consistency, completeness, accuracy, reasonableness) and recommend target-state improvements.
- Draft technical guidelines, documentation, and presentations to effectively communicate complex AI concepts, project status, and results to both technical and non-technical stakeholders.
- Ensure compliance with data protection and AI Act regulations.
- Implement MLOps practices to automate the machine learning lifecycle, including continuous integration, delivery, and monitoring (CI/CD/CD) of models.
- Monitor model performance in production, identifying model drift and initiating retraining processes to maintain accuracy and relevance.
- Stay abreast of the latest academic and industry research in AI/ML to propose and pilot innovative solutions that provide competitive advantage.
- Excellent knowledge of programming languages essential for AI/ML, primarily Python and R, and their key libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas, SpaCy, NLTK).
- Excellent knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, and/or artificial intelligence frameworks.
- Excellent knowledge of generative AI, small and large language models.
- Excellent knowledge of data management principles, including data governance, data quality, data cleaning, and data lifecycle management for AI projects.
- Good knowledge of cloud tools for Fine tuning or training Models, like AWS SageMaker or Azure Machine Learning Studio.
- Good knowledge of cloud platforms for building LLM solutions (e.g., AWS Bedrock, Azure AI Studio) and frameworks for orchestration (e.g., LangChain, LlamaIndex) and safety/guardrails.
- Good knowledge of AI Agent Orchestration frameworks, like Langchain or Semantic Kernel.
- Good knowledge of natural language processing systems lifecycle and agile software development methodologies.
- Good knowledge of quality assurance and quality control for machine translation (MT) and experience with MT quality procedures, testing methodologies and tools, such as automatic quality metrics (BLEU scores and similar) and human evaluation of MT quality.
- Knowledge of query languages, such as SQL, Hive, Pig, etc and with information extraction.
- Knowledge of NoSQL databases, such as MongoDB, Cassandra, HBase, etc.
- Knowledge of data visualisation tools, such as D3.js, GGplot, etc.
- Experience in the field of corpus based linguistics.
- Experience with alignment models and classification methods.
- Experience with data analytics over big datasets, non-structured databases as well as data lakes.
- Knowledge of relevant elements of cybersecurity of AI systems
- Knowledge of the relevant aspects of the AI Act and AI risks.
- Experience with MLOps practices and tools for model versioning, deployment, monitoring, and governance (e.g., MLflow, Kubeflow).
- Knowledge of techniques for responsible AI, including bias detection and mitigation (e.g., IBM AIF360, Fairlearn) and model explainability (e.g., SHAP, LIME).
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Languages
English level C1
Location
Brussels, Belgium
Work mode
Hybrid (on-site at Brussels offices + remote)
What can you expect from us?
Mind-blowing workplace culture. You will be integrated in a professional, dynamic and collaborative team.
100% Remote opportunities
We want you to have the flexibility to work where you feel most comfortable and productive.
International Career
- You can expect professional growth and to be connect with the world.
- We are represented in Portugal, Belgium, Luxembourg, and Denmark.
- And with projects in many other countries: Netherlands, Luxembourg, Singapore and in the United States of America (and a lot more is coming…)
If you wish to work with us and you are outside European Union (good news…) we are a Tech Visa Company, We will help!
As a plus, we provide Health and Life Insurance.
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