Machine Learning Engineer, Platform

About This Opportunity

We are representing a confidential AI platform organization seeking a Machine Learning Engineer, Platform in London. Our client is building production-grade agentic AI systems for enterprise and government customers, focusing on the infrastructure and tooling that power intelligent applications at scale.

This role centers on context and memory capabilities within the platform—including knowledge bases, vector stores, RAG pipelines, and context engines. You'll own hard technical problems end to end, from research and prototyping through production deployment, working on systems that deliver real impact for enterprise customers.

Responsibilities

• Own large areas of the platform end to end, from design through to production deployment
• Work on 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 that support ML and LLM components in production
• Deliver experiments and new capabilities quickly, maintaining high quality and tight feedback loops with customers
• Collaborate across product, ML, and infrastructure teams to shape the direction of the platform

What We're Looking For

• 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, knowledge representation, and semantic search
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints
• Strong communication skills and comfort working in customer-facing or cross-functional environments
• Experience scaling products at hyper-growth startups

How We Work With You

When you apply through Get A Job.ai, our talent team reviews your profile and conducts an initial screening. If there's a strong match, we submit your candidacy to our client for consideration. Throughout the process, we serve as your advocate and guide. Please do not contact the client directly—all communication flows through our recruiting team to ensure the best possible experience.

Pay

Compensation details will be discussed during the screening process with our recruiting team.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome candidates from all backgrounds and work to ensure fair consideration regardless of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other protected characteristic.