Scale AI
Machine Learning Engineer, Platform
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Machine Learning Engineer, Platform
Machine Learning Engineer, Platform
Location: London, UK
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.
About the Role
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.
Key Responsibilities
You will:
- Own large areas of the platform end-to-end, driving components 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 while maintaining high quality and tight feedback loops with customers.
- Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.
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Ideal Candidate
Candidates should ideally have: → 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 in Computer Science, Machine Learning, AI, or equivalent practical experience. → A 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 writing production-quality, testable, and maintainable code. → Experience scaling or shipping products at high-growth startups. → The ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints. → Strong communication skills and comfort working in cross-functional environments.
About Scale
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.
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Workplace Culture
We believe that everyone should be able to bring their whole selves to work. We are committed to being an inclusive and equal opportunity workplace, ensuring equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity, or Veteran status.
Commitment to Accessibility: We comply with accessibility standards. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact: accommodations@scale.com.
Data Collection Policy
We collect, retain and use personal data for professional business purposes, including notifying you of job opportunities and collaborating with affiliates. Any information collected will be treated in accordance with our internal policies. Refer to our privacy policy for additional information.
Note
We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role to ensure a fair and thorough evaluation of all applicants.
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