machine learning engineer for enterprise AI platforms

Scale GP is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and agentic workflows. Scale develops reliable AI systems, high-quality data, and full-stack technologies that help leading models, enterprises, and governments build, deploy, and oversee AI applications.

• Own large areas of the platform end to end, driving components from design through production deployment;
• Develop knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data;
• Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking;
• Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services;
• Develop context retrieval systems that balance recall, precision, latency, and cost;
• Build evaluation frameworks, datasets, and metrics to measure retrieval quality, context relevance, and end-to-end agent performance;
• Build reliable backend services and data pipelines supporting ML and LLM components in production;
• Deliver experiments and new capabilities quickly while maintaining high quality and tight feedback loops with customers;
• Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.

• 5+ Years of experience building and deploying machine learning or AI systems for real-world production use cases;
• Strong engineering fundamentals supported by a Master’s or PhD degree in Computer Science, Machine Learning, AI, or equivalent practical experience;
• Deep, hands-on understanding of retrieval systems, RAG, embeddings, vector indexing, and knowledge representation;
• Experience with knowledge representation, semantic search, or agentic systems;
• Proven proficiency in Python, including production-quality, testable, and maintainable code;
• Experience scaling or shipping products at high-growth startups;
• Ability to operate in ambiguous problem spaces while balancing research-driven approaches with pragmatic product constraints;
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

• Office role in London, England, United Kingdom;
• Inclusive and equal opportunity workplace;
• Reasonable accommodations are available to applicants with physical and mental disabilities;
• A 90-day waiting period applies before reconsideration for the same role.