AI Engineer - Internship
Published on 11/02/2026
Banque Internationale à Luxembourg (BIL)
- Luxembourg, Luxembourg (Canton)
- Banking
Founded in 1856, Banque Internationale à Luxembourg is the oldest multi-business bank in the Grand Duchy. From its foundation, the BIL has always played an active role in the development of the Luxembourg economy. It currently operates in retail, private and corporate banking, as well as on major capital markets. Employing more than 2 000 people, BIL is present in the financial hotspots that are Luxembourg, Switzerland, and China.
As a major player in Luxembourg's finance industry and as a signatory of the UN Principles of Responsible Banking, BIL is committed to handing over a responsible and sustainable bank to future generations.
Mission
You will support the Head of CoE Data & AI Modeling and the Advanced Analytics team in designing, developing, and operationalising AI solutions across the bank. Your work will contribute directly to the transformation of BIL's data landscape through intelligent automation, document understanding, and the industrialisation of machine learning and LLM-based systems.
The role is highly technical and hands-on, sitting at the intersection of software engineering, data science, and operational excellence. Curiosity, pragmatism, and strong engineering discipline are all essential.
You will help make AI delivery faster, more robust, and more reliable by (i) developing and testing AI components, (ii) automating model deployment workflows, and (iii) preparing committee-ready documentation and technical materials.
Main duties
1. AI model development & experimentation
* Build and refine components for OCR, classification, text extraction, and LLM-based retrieval.
* Clean and prepare datasets for model training (unstructured documents, metadata, historical archives).
* Evaluate model performance through structured metrics and testing frameworks.
* Document experiments, results, and lessons learned.
2. AI pipelines & automation
* Contribute to the development and maintenance of MLOps pipelines.
* Automate recurring data processing tasks in Python & SQL (ETL, preprocessing, Document processing, …).
* Help integrate models into bank workflows via APIs, microservices, or orchestration tools.
* Support the migration of prototypes into stable, production-ready components.
3. LLM engineering & prompt optimisation
* Test and evaluate large language models.
* Develop prompt templates, retrieval strategies, and evaluation datasets.
* Contribute to AI use cases such as document summarisation, classification, and Q&A systems.
* Assist in integrating Snowflake Cortex or Dataiku LLM Mesh features into real use cases.
4. AI governance & documentation
* Prepare governance-ready materials: model cards, risk assessments, validation notes.
* Ensure traceability of datasets, parameters, evaluation logic, and deployment versions.
* Assist in producing committee-ready PowerPoint packs for project progress and decision-making.
5. Ad hoc analytical & engineering support
* Contribute to deep-dives on performance issues, error analysis, or model drift.
* Support internal teams by preparing demos, tests, and technical proofs-of-concept.
* Participate in workshops with compliance, risk, and business stakeholders when relevant.
Profile
* Student in Data Science, AI Engineering, Computer Science, Applied Mathematics, or a related field (minimum Master 1).
* Alternatively, a strong engineering or quantitative finance student with demonstrated coding capability in Python and a clear interest in AI/ML.
Technical skills
* Python (advanced): pandas, NumPy, scikit-learn, regex, model evaluation.
* Machine Learning / NLP basics: vector embeddings, classification, model metrics.
* LLM familiarity: prompt engineering, LangChain, retrieval techniques - strong asset.
* OCR & document processing: Tesseract/OpenCV/PyPDF/PDF processing - asset.
* MLOps foundations: Git, CI/CD, containerisation, APIs - plus.
* Data tools: Snowflake, Dataiku, SQL. - strong asset.
* PowerPoint: ability to synthesise and structure clear technical presentations.
Knowledge of banking processes, credit risk, or financial documents (contracts, balance sheets, KYC documents) would be considered a strong advantage.
Working style
* Strong attention to detail and disciplined coding practices.
* Ownership mindset: able to progress tasks independently once aligned on objectives.
* Pragmatic approach: focus on usable, robust, and well-documented outputs.
* Curiosity and willingness to explore new technologies within a structured framework.
* Professionalism and discretion when handling confidential data.
BIL offers a wide range of challenging AI and data projects and diverse career paths. We will assist you in identifying the opportunity that best matches your skills and aspirations. Your personal development is our priority, and we strongly encourage you to explore different areas of the bank for a broad and enriching experience.
BIL firmly believes that diversity & inclusion foster collective performance. We are committed to creating a culture of inclusion that encourages individual development with equal opportunities for all.
NB: The selected candidate will be asked to provide an extract from the criminal record (no. 3) as evidence of integrity and justified with regard to the specific needs of the position to be filled. Other documents will be collected, to the extent legally permitted, to perform background checks.
BIL offers a broad range of challenging projects and a huge choice of career paths .We will assist you in finding the one that best meets your skills and expectations. Your personal development is our priority and we greatly encourage you to dive into different business areas for the broadest possible experience.
BIL is firmly of the opinion that diversity & inclusion contribute towards increasing the collective performance of the Bank. We are committed to creating a culture of inclusion that encourages individual development with equal opportunities for all.
NB: The selected candidate will be asked to provide an extract from the criminal record (no.3) as evidence of integrity and justified with regard to the specific needs of the position to be filled. Other documents will be collected, to the extent legally permitted, to perform background checks.
