Machine Learning Engineer / AI Engineer (MLOps & Deployment). AQES-B11125.
Core
Industrialize and deploy Machine Learning, Deep Learning, RAGs, and GenAI agents into production, ensuring reliability, scalability, and governance throughout the lifecycle.
Role type
Senior MLOps Engineer (Production Deployment)
Builds
Production-ready ML and GenAI services for an insurance company
Domain
Insurance / Artificial Intelligence / MLOps
Deliverable
production ML models
Required skills
Python (backend/ML), API design (FastAPI/Flask), Docker, Kubernetes, CI/CD pipelines, model versioning, observability (logs/metrics/traces), LLM integration, Responsible AI compliance
Preferred skills
Experience with RAG architectures, agent deployment, drift detection, canary/blue-green deployments
Technologies
Python, FastAPI, Flask, Docker, Kubernetes, LLMs
Responsibilities
Design and operate inference services with defined SLAs; Build and maintain training and inference pipelines; Define monitoring strategies for drift detection and quality control; Ensure end-to-end observability and SLOs; Manage secure deployments; Integrate and operate external LLM providers; Ensure compliance with EU AI Act and privacy regulations
Seniority
Senior, hands-on IC
