aimlroles

AI / ML Engineer - Senior IT profile

Cronos Europa cronoseuropa.com Open · verified Oct 22, 2026
Luxembourg Full-time Senior Machine Learning Engineering

At a glance

Senior Machine Learning Engineering role at Cronos Europa. Luxembourg · full-time.

Pay not stated Machine Learning Engineering salary

RoleMachine Learning Engineering
SenioritySenior
LocationLuxembourg
EmploymentFull-time
PostedSep 29, 2026 · 3w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build, train and support NLP and AI applications, including generative AI and language models for defined use cases
  • Deploy generative models or connect their APIs, then use RAG and build classifiers with selected features
  • Improve machine-translation quality for each language pair through testing, evaluation and longer-term quality plans
  • Set data rules with stewards and IT teams, then build checks for data quality, integrity and bias
  • Design NLP and ML architectures, automate model delivery and monitoring, and track production drift for retraining

What you bring

  • At least ten years working in IT
  • Strong Python and R skills, with experience using core machine-learning libraries and algorithms
  • Deep knowledge of generative AI, language models and data governance for AI work
  • Good knowledge of cloud-based model training and LLM platforms, plus orchestration and safety tools
  • English communication skills, spoken and written; French is an additional asset

Who this fits

This suits a senior AI/ML engineer who can work across NLP, machine translation, data quality and production model operations. The role is on-site and offers either freelance work or an employment contract.

From the employer

  • AI / ML Engineer - Senior IT profile

We are currently looking for an AI/ML Engineer to strengthen the Cronos Europa team.

  • Full-time
  • Freelance and Employment contract
  • On-site

Responsabilities:

  • 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.

Technical skills:

  • 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).

Profile:

  • Optional: One of the following or an equivalent certification: AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, SAS Certified Professional AI and Machine Learning.
  • Ability to understand, speak and write English, optionally French as an additional
    asset.
  • Minimum 10 years of experience in IT

Why Cronos Group?

We’ll propose you:

  • An attractive salary package
  • A good work-life balance environment
  • The assurance of working in cutting-edge technologies in an entrepreneurial spirit.
  • The opportunity to develop your skills thanks to tailor-made training courses according to your needs
  • A good job in a friendly place

If you wish to integrate a dynamic structure on a human scale while working with the latest technologies, don't wait anymore and join Cronos!