1 month ago
Luxembourg, LuxembourgSenior
Responsibilities
- Design, develop, and maintain data pipelines and data products for analytics and AI.
- Help define and optimize hybrid on-premise and cloud data architectures.
- Develop, deploy, and supervise machine learning models for fraud, AML/KYC, commercial performance, and document analysis.
- Implement generative AI and LLM solutions including OCR, document classification, information extraction, and RAG.
- Industrialize development through CI/CD, MLOps, and API integration practices.
- Ensure model quality, traceability, monitoring, and compliance with AI governance requirements.
- Write technical documentation and participate in validation committees.
- Collaborate with business, IT, compliance, and risk teams.
- Contribute to transformation projects and support more junior team members.
Requirements
- Higher education or equivalent training in computer science, data, AI, mathematics, or a related field.
- At least 5 years of experience in data engineering, data science, or AI, ideally in a regulated environment.
- Strong proficiency in Python, SQL, and Git.
- Solid knowledge of machine learning, NLP, and model evaluation.
- Experience with Dataiku, Snowflake, or Big Data platforms.
- Experience industrializing solutions and deploying them to production.
- Fluency in French and English.
- Experience with LLMs, prompt engineering, and LangChain is appreciated.
- Knowledge of OCR and document processing is appreciated.
- Knowledge of DevOps/MLOps concepts including containers, orchestration, and CI/CD is appreciated.
- Understanding of banking, regulatory, and AML/KYC topics is appreciated.
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