- Company Name
- DHM IT
- Job Title
- Ingénieur·e MLOps IA / LLM (H/F)
- Job Description
-
**Job Title**
ML Ops Engineer – AI / LLM (M/F)
**Role Summary**
Responsible for industrialising, securing and deploying AI/ML models—including large language models, retrieval‑augmented generation, NLP and computer vision pipelines—within a production environment. Works across data science, development, and operations teams to transition prototypes into reliable, scalable services.
**Expectations**
* Minimum 3 years of hands‑on MLOps or production‑level AI/ML deployment experience.
* Proven ability to design end‑to‑end pipelines (training ➜ deployment) with strong focus on reliability, reproducibility and observability.
* Agile mindset; collaborative across product, data, and engineering stakeholders.
* Strong analytical mindset with attention to detail and quality.
**Key Responsibilities**
* Design, implement and maintain robust, traceable pipelines for model training, testing, versioning, and deployment.
* Automate CI/CD workflows using GitLab, Docker, and other orchestration tools; manage model and dataset versioning (MLflow, Comet ML).
* Integrate monitoring, drift detection, feedback loops, and human‑in‑the‑loop mechanisms for continuous model health.
* Lead model optimisation practices (quantization, distillation, LoRA, pruning) where appropriate.
* Partner with data‑science teams to translate research prototypes into production‑ready services.
* Document best practices, create knowledge bases, and foster a culture of industrialisation across cross‑functional teams.
**Required Skills**
* Python programming with NumPy, Pandas, scikit‑learn, PyTorch or TensorFlow.
* SQL for data acquisition and manipulation.
* MLOps tooling: GitLab CI/CD, Docker, MLflow, Comet ML, model & data versioning.
* LLM & NLP frameworks: LangChain, LangSmith, Semantic Kernel, RAG architecture.
* Cloud deployment on AWS, GCP or Azure; experience with serverless or containerised services.
* Optional: Kubernetes, Kubeflow, Argo for orchestration; Computer Vision and small‑language‑model expertise are advantageous.
* Soft skills: strong documentation, knowledge transfer, autonomous decision‑making, inter‑team collaboration, and curiosity about advanced AI use‑cases.
**Required Education & Certifications**
* Bachelor’s (or higher) degree in Computer Science, Data Science, Engineering, or related technical field **or** equivalent professional experience.
* Certifications in cloud platforms (AWS, GCP, Azure) or MLOps tooling are a plus.
Neuilly-sur-seine, France
Hybrid
Junior
15-12-2025