Machine Learning Engineer, Platform

<p><strong>Machine Learning Engineer, Platform</strong></p> <p>London, UK</p> <p>Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and agentic workflows. We are looking for a Machine Learning Engineer to join our team and build the retrieval and knowledge representation systems at the heart of the platform. You will own ML components end to end — from research and prototyping through to production deployment — working across knowledge bases, vector stores, RAG pipelines, and context engines to power agents that deliver real impact for enterprise customers.&nbsp;</p> <p><strong>You will:</strong></p> <ul> <li>Own large areas of platform end to end, driving components from design through to production deployment.</li> <li>Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data.</li> <li>Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking.</li> <li>Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services.</li> <li>Develop context retrieval systems that balance recall, precision, latency, and cost.</li> <li>Build evaluation frameworks, datasets, and metrics to measure retrieval quality, context relevance, and end to end agent performance.</li> <li>Build reliable backend services and data pipelines that support ML and LLM components in production.</li> <li>Deliver experiments and new capabilities quickly, maintaining high quality and tight feedback loops with customers.</li> <li>Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.</li> </ul> <p><strong>Ideally you'd have:</strong></p> <ul> <li>5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.</li> <l