Scale AI Logo

Scale AI

Machine Learning Engineer, Platform

Posted 7 Days Ago
Be an Early Applicant
In-Office
London, Greater London, England, GBR
Senior level
In-Office
London, Greater London, England, GBR
Senior level
Build and operate core retrieval and knowledge representation systems for a generative AI platform: design RAG pipelines, embeddings, indexing, vector-store integrations, knowledge graphs/ontologies, evaluation frameworks, and production ML backend services while collaborating across product, ML, and infra teams and shipping enterprise-grade features.
The summary above was generated by AI

Machine Learning Engineer, Platform

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. 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. 

You will:

  • Own large areas of 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, maintaining high quality and tight feedback loops with customers.
  • Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.

Ideally you'd 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 degree 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 customer-facing or cross-functional environments.

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

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. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to 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. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Similar Jobs

2 Days Ago
Hybrid
London, England, GBR
Senior level
Senior level
Fintech • Mobile • Payments • Software • Financial Services
Build a greenfield ML lifecycle platform for financial crime detection: design declarative training pipelines, model packaging/serving, evaluation frameworks, monitoring and drift detection, and integrate with central ML infrastructure to improve data scientist productivity and ensure regulatory auditability.
Top Skills: AirflowContainer-Based DeploymentJavaKotlinKubeflowMlflowOnnxPythonSQL
7 Days Ago
In-Office
London, Greater London, England, GBR
Senior level
Senior level
Food • Logistics • Transportation
Design, build, and scale a centralised ML platform for training, validation, deployment, model serving, and feature stores. Develop infrastructure, tooling, libraries, and best practices (MLOps) while collaborating with product and data science teams to automate, document, and operationalise ML workflows.
Top Skills: Aws EcsAws EksAws LambdaGoKafkaKubernetesLlmsMetaflowPythonPyTorchScikit-LearnTensorFlowTerraform
7 Days Ago
In-Office
London, Greater London, England, GBR
Senior level
Senior level
Food • Logistics • Transportation
Build and scale a central ML platform to enable training, validation, deployment, and serving of models. Design platform direction, develop pipelines, feature stores, and libraries, automate operations, collaborate with product and data science teams, and drive MLOps best practices and tooling across the company.
Top Skills: Aws EcsAws EksAws LambdaGoKafkaKubernetesLlmsMetaflowMlopsPythonPyTorchScikit-LearnTensorFlowTerraform

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account