AI / ML Engineer - Senior IT profile

Luxembourg, LU

Live, first seen by us 37 days ago

Pay: Pay not listed
Work setting: On-site — work setting source
Freelance and Employment contract On-site Responsabilities:
Read the full posting
Employment: Full-time — employment source
We are currently looking for an AI/ML Engineer to strengthen the Cronos Europa team. Full-time Freelance and Employment contract
Employment type in the employer’s posting: Full-Time
From the employer’s posting

What you’ll work on

Full posting

Develop, train and maintain NLP and generative AI models and applications
Deploy generative AI models or their APIs, using retrieval augmented generation (RAG)
Improve machine translation quality and build systematic MT evaluation
Implement MLOps CI/CD pipelines and monitor models for drift and retraining
Define data quality controls and detect and mitigate bias in datasets and models

From the employer’s posting

Develop, train, and maintain machine learning models and software applications in the fields of Natural Language Processing (NLP) and Artificial Intelligence (AI)

Deploy generative AI models or integrate their APIs, and Retrieval Augmented Generation (RAG) techniques

Perform studies and developments aiming at improving the quality of machine translation (MT) engines for each installed language pair

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

Define data controls and implement strategies to ensure data quality, integrity, and the detection and mitigation of bias in datasets and AI models.

What you’ll bring

All qualifications

Core experience

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).
Ability to understand, speak and write English, optionally French as an additional asset.
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.

Qualification wording

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).

Ability to understand, speak and write English, optionally French as an additional asset.

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.

Apply at Cronos Europa

Posting record

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Status in our records: Live
First seen by us: Sep 28, 202637 days ago
Recorded sightings: 54
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 37

Similar jobs usually come down between day 6 and day 69.

Well past Cronos Europa’s usual: its jobs come down by about day 15.

From 4,387 similar postings that came down, and 12 of Cronos Europa’s. Coming down is not always a hire.

Cronos Europa is hiring

8 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring at a steady pace
Takes jobs down quickly

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
R
SAS
SQL
AWS
Azure
Hive
MLflow
MongoDB
NoSQL
SageMaker
pandas
PyTorch
scikit-learn
TensorFlow

Where the posting names them

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.

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.

- 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.

- 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 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.

- 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).

- 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.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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!

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