Machine Learning Engineer

Job Title: ML Engineer – GenAI / LLM / Azure Location: London, Canary Wharf, UK Work Mode: Hybrid – 3 Days Onsite per Week Contract Duration: 12 Months • Overview: We are seeking an experienced ML Engineer with strong expertise in Azure, Generative AI, and Large Language Models (LLMs) to join a high-performing AI engineering team delivering enterprise-scale intelligent solutions. The ideal candidate will have hands-on experience in designing, deploying, and optimizing AI/ML systems, with particular focus on GenAI applications, RAG architectures, model lifecycle management, and scalable MLOps practices. Key Responsibilities: • Design, develop, and deploy scalable AI/ML solutions using Azure cloud technologies • Build and optimize LLM-based applications and Generative AI solutions • Develop Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise data sources • Fine-tune pretrained LLMs using PEFT methodologies including LoRA and QLoRA • Design and maintain robust ETL/ELT data pipelines for AI model training and inference • Implement AI model monitoring, performance tuning, versioning, and lifecycle management • Build and manage automated CI/CD pipelines for model deployment and retraining workflows • Collaborate closely with Data Scientists, DevOps Engineers, and business stakeholders during the end-to-end model development lifecycle • Deploy containerized AI applications using Docker and Kubernetes • Ensure AI solutions comply with Responsible AI principles including fairness, transparency, governance, and security standards • Support infrastructure provisioning and optimization across cloud-based AI environments • Maintain technical documentation and contribute to best practices for scalable AI engineering Required Skills and Experience: • 5+ years of experience in Machine Learning Engineering or AI Engineering • Strong hands-on experience with Microsoft Azure • Proven experience working with Large Language Models (LLMs) and Generative AI solutions • Experience building and deploying RAG architectures • Expertise in MLOps, CI/CD pipelines, and model deployment strategies • Experience with Docker and Kubernetes • Strong Python programming skills • Experience with model monitoring, observability, and performance optimization • Familiarity with vector databases and embedding workflows • Strong understanding of AI governance and Responsible AI practices Nice to Have: • Experience within the Insurance domain • Exposure to Agentic AI systems and autonomous AI workflows