Our client is looking for an AI Specialist
Description
In the context of this mission, you will join an ICT team and contribute to the design, development, and production deployment of AI/GenAI solutions: business assistants, document automation, Retrieval Augmented Generation (RAG), information extraction, classification, detection and image analysis (Computer Vision), as well as the training and evaluation of models. You will be responsible for the complete chain from ideation and prototyping to industrialization (MLOps/LLMOps), with a strong focus on quality, security, compliance and maintainability.
- Azure AI: management and integration of Azure AI services (Azure OpenAI / Azure AI Services), orchestration and deployment via Azure AI Foundry (or equivalent services), management of endpoints, quotas, monitoring and costs.
- LLM & GenAI: prompt engineering, patterns (RAG, function calling/tools, agents), evaluation and quality improvement (guardrails, grounding, hallucinations), management of contexts and embeddings.
- Hugging Face: use of pre-trained models, fine-tuning (PEFT/LoRA where applicable), dataset management, pipelines and deployments.
- Training of “classic” models: supervised/unsupervised models (classification, regression, clustering), feature engineering, metrics, validation and interpretability.
- Computer Vision: dataset preparation, training/evaluation (detection, segmentation, OCR if applicable) and integration into application pipelines.
- Copilot: experience with Copilot Studio (creation of assistants/agents, connectors, governance) and understanding of the possibilities/constraints of Copilot for Microsoft 365.
- DevOps/MLOps/LLMOps: CI/CD, versioning (code/data/models), automated tests, traceability, observability (logs/metrics/traces), environment management and secure deployments.
Tasks and responsibilities:
- Analysis of business needs and translation into relevant and measurable AI/GenAI use cases.
- Design of AI architectures (cloud/hybrid) including storage, data pipelines, Azure AI services and consuming applications.
- Preparation, cleaning and governance of data (quality, anonymization/pseudonymization if necessary).
- Development of prototypes and POCs, then industrialization into robust solutions (APIs, microservices, integrations).
- Training, fine-tuning and evaluation of models (LLM and ML/CV models), definition of metrics and acceptance criteria.
- Implementation of MLOps/LLMOps practices: pipelines, monitoring, drift, re-train, versioning and rollback.
- Implementation of security and compliance measures (access controls, secret management, data protection, AI governance).
- Technical documentation, knowledge transfer, support of teams (mentoring, guidelines, best practices).
Technical skills
- Python (development, data science, packaging) — ≥ 5 years
- “Classic” Machine Learning (supervised/unsupervised, metrics, validation) — ≥ 5 years
- Deep Learning (PyTorch or TensorFlow/Keras) — ≥ 5 years
- LLM / GenAI (prompting, RAG, embeddings, evaluation) — ≥ 2 years
- Azure AI (Azure OpenAI / Azure AI Services): integration & deployment — ≥ 2 years
- Azure AI Foundry (or equivalent): orchestration, endpoints, monitoring/costs — ≥ 2 years
- MLOps / LLMOps (CI/CD, versioning of models & data, monitoring, reproducibility) — ≥ 2 years
- Basic data engineering (SQL, REST API, …) — ≥ 2 years
- Computer Vision (classification/detection or OCR) — ≥ 5 years
- Git + collaboration practices — ≥ 5 years
- AI security & governance — at least some experience
- Language 1: French or Dutch — C1 level
- Language 2: French or Dutch (the other language) — B1 level
- Language 3: English — B2 level
- Scoping and steering of AI projects: ability to define scope, objectives, deliverables and coordinate stakeholders until production deployment — ≥ 2 years
Soft Skills
- Knowledge of the company, the IT world, and understanding of the challenges of the role
- Understanding of the company's mission and core activities
- Ability to integrate into the company teams through values: kindness, courage, positivity, reliability
- Presentation skills
- Professional attitude
- Correctness and respect towards management
- Clear and effective communication
- Responsible commitment for the duration of the contract
