Job Description
We are seeking an MLOps / AI Engineer to bridge the gap between experimental data science and production-grade systems. This role sits at the core of building scalable AI solutions, with a strong focus on LLMs, agentic workflows, and end-to-end ML pipelines.
You'll work across the full lifecycle from concept to deployment partnering with data scientists, engineers, and infrastructure teams to deliver production-ready AI systems.
What You'll Do
- Design, build, and deploy end-to-end machine learning pipelines
- Operationalise LLMs, embeddings, and multi-agent systems in real-world environments
- Develop and maintain scalable data pipelines and model lifecycle workflows (training, validation, deployment)
- Build production-grade RAG systems and AI-driven applications
- Manage model performance, monitoring, and data drift in production
- Containerise applications using Docker and deploy via Kubernet...