- Company Name
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- Job Title
- Ingénieur en Intelligence Artificielle
- Job Description
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Job title: AI Engineer
Role Summary
Lead the design, development, and production deployment of AI/ML components for a next‑generation virtual assistant platform. Create autonomous AI agents that understand business context, execute multi‑step workflows, and integrate LLMs, knowledge graphs, and speech technologies into scalable, maintainable production systems.
Expactations
* ≥5 years as an AI Engineer, ML Engineer, AI Research Engineer, or Data Scientist focused on production AI.
* Proven expertise in LLM fine‑tuning, prompting, RAG, and agent architecture (LangChain, LlamaIndex, etc.).
* Strong background in Python, ML/DL libraries, and container‑based cloud deployment (Azure, Docker, Kubernetes).
* Ability to collaborate closely with data, backend, and product teams while owning architectural decisions.
Key Responsibilities
* Design, prototype, and deploy autonomous AI agents that plan and execute complex workflows for professional users.
* Integrate cutting‑edge LLMs, knowledge graphs, and TTS/STT modules into end‑to‑end architectures (RAG + fine‑tuning + agents + graph + speech).
* Ensure models meet performance, scalability, security, and traceability requirements in cloud production.
* Maintain CI/CD pipelines, version control, and automated testing for AI services.
* Evaluate and incorporate research advances into production systems, balancing innovation with operational robustness.
* Validate new technical approaches with rapid experiments and stakeholder feedback.
Required Skills
* Deep proficiency in Python and ML/DL frameworks (PyTorch, TensorFlow, Hugging Face).
* Extensive experience with LLM operations (fine‑tuning, prompting, RAG, LLMOps).
* Knowledge of cloud AI data architectures (data lakes, feature stores, vector databases).
* Strong statistical modeling and evaluation methods.
* Linux proficiency and container orchestration with Docker & Kubernetes.
* Advanced Git usage, CI/CD practices, and release management.
* Excellent communication with cross‑functional teams (Data, Backend, Product).
* (Preferred) Experience with Neo4j/knowledge graphs, LangChain, AutoGPT, CrewAI, MCP, model optimization (quantization, pruning), vector DBs (Qdrant), Databricks, and SaaS/multi‑tenant contexts.
Required Education & Certifications
* Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field (preferred).
* Relevant certifications in cloud AI services (Azure AI, AWS ML, etc.) are a plus.