
Medior Data & AI Engineer
- Luxemburg
- Unbefristet
- Vollzeit
- Design and implement AI pipelines that handle end-to-end ML workflows: data collection, preparation, training, deployment, and monitoring
- Develop and deploy LLMs - including open-source models (e.g., Mistral, LLaMA) - on both cloud and on-premises infrastructure, ensuring performance and data privacy
- Engineer NLP-based solutions for information extraction, classification, semantic search, and document enrichment
- Build and expose ML models via production-ready APIs using FastAPI or equivalent frameworks
- Manage AI workloads on cloud platforms (Azure or AWS) as well as on embedded edge devices (e.g. NVIDIA Jetson Orin, Xavier NX) for real-time inference.
- Implement Infrastructure-as-Code (e.g., Terraform, Ansible) to automate ML platform deployment
- Integrate AI services into event-driven and serverless architectures (e.g., Azure Functions, Event Grid).
- At least 2 years in AI/ML engineering, with proven experience in:
- Programming & APIs: Python, RESTful service design
- NLP & ML: Transformers, open-source LLMs (Mistral, LLaMA, etc.), model fine-tuning, prompt engineering, Text classification & enrichment, OCR & document understanding, Retrieval-Augmented Generation (RAG), chatbot development, vector search and embeddings.
- Cloud Platforms: Azure (Functions, AI Services, Logic Apps), AWS (Glue, Step Functions)
- Infrastructure Automation: Terraform, Ansible, Docker, GitHub Actions.
- Familiarity in the following techs/domains is a plus:
- Managed LLM platforms (eg: Azure OpenAI Service)
- Event-driven architectures (eg: Service Bus, Event Grid)
- Hybrid architectures (cloud/on-prem integration)
- Edge AI: NVIDIA Jetson AGX Orin, Xavier NX, Ollama runtime for local LLM inference
- Real-time video analysis via computer vision.
- Interest or background in traditional software development (e.g., Java, .NET, TypeScript, Spring Boot) is a big plus
- Any AWS/Azure certification is optional but valued.
- Good communication in either English or French
- Strong documentation habits and strategic thinking
- Agile/DevOps culture familiarity.